computer research scientist skills

Computer and Information Scientists

Science, Technology, Engineering and Mathematics
Income and Hiring
Tasks, Knowledge, Skills
Career Insights

What tasks do Computer and Information Scientists perform?

Analyze problems to develop solutions involving computer hardware and software.

Apply theoretical expertise and innovation to create or apply new technology, such as adapting principles for applying computers to new uses.

Assign or schedule tasks to meet work priorities and goals.

Meet with managers, vendors, and others to solicit cooperation and resolve problems.

What do Computer and Information Scientists need to know?

Computers and electronics.

Knowledge of circuit boards, processors, chips, electronic equipment, and computer hardware and software, including applications and programming.

Mathematics

Knowledge of arithmetic, algebra, geometry, calculus, statistics, and their applications.

Engineering and Technology

Knowledge of the practical application of engineering science and technology. This includes applying principles, techniques, procedures, and equipment to the design and production of various goods and services.

What skills do Computer and Information Scientists need?

Judgment and decision making.

Considering the relative costs and benefits of potential actions to choose the most appropriate one.

Complex Problem Solving

Identifying complex problems and reviewing related information to develop and evaluate options and implement solutions.

Critical Thinking

Using logic and reasoning to identify the strengths and weaknesses of alternative solutions, conclusions, or approaches to problems.

You might also be interested in…

Computer hardware engineers, biochemists and biophysicists, molecular and cellular biologists, aerospace engineers.

Data on career profiles are based on information supplied by the O*NET Program , sponsored by U.S. Department of Labor, Employment, and Training Administration.

How to become a computer and information research scientist

Is becoming a computer and information research scientist right for me.

The first step to choosing a career is to make sure you are actually willing to commit to pursuing the career. You don’t want to waste your time doing something you don’t want to do. If you’re new here, you should read about:

Still unsure if becoming a computer and information research scientist is the right career path? Take the free CareerExplorer career test to find out if this career is right for you. Perhaps you are well-suited to become a computer and information research scientist or another similar career!

Described by our users as being “shockingly accurate”, you might discover careers you haven’t thought of before.

How to become a Computer and Information Research Scientist

Becoming a computer and information research scientist requires a combination of education, research experience, and specialized skills. Here are the general steps to pursue a career in this field:

Obtain a Bachelor's Degree: Start by earning a Bachelor's Degree in Computer Science , Information Technology , or a related field. Ensure that the program you choose includes coursework in algorithms, programming languages, data structures, mathematics, and computer systems.
Gain Research Experience: Seek opportunities to engage in research projects during your undergraduate studies. Join research groups, work as a research assistant, or participate in summer research programs to gain hands-on experience in conducting research, working with data, and developing technical skills.
Pursue a Graduate Degree: While a bachelor's degree may be sufficient for some entry-level positions, a master's degree or Ph.D. is often required for research scientist roles. Consider pursuing a graduate program in computer science or a specialized area of interest within the field. Graduate programs provide advanced coursework, research opportunities, and mentorship from faculty members.
Select a Specialization: Determine your area of interest within computer and information science. This could be artificial intelligence , cybersecurity , data science , human-computer interaction , or another specialized field. Tailor your coursework, research projects, and internships to align with your chosen specialization.
Engage in Research Projects: Actively participate in research projects during your graduate studies. Collaborate with faculty members, research centers, or industry partners to gain practical research experience, contribute to publications, and build a strong research portfolio. Seek opportunities to present your work at conferences or publish research papers.
Develop Technical Skills: Acquire technical skills relevant to your research area. Stay updated with the latest advancements, programming languages, algorithms, and tools used in your field of interest. Develop proficiency in data analysis, programming, machine learning frameworks, and other specialized tools or software.
Network and Collaborate: Attend conferences, workshops, and seminars to network with experts in your field. Engage in discussions, seek mentorship, and explore collaboration opportunities with researchers and professionals in academia, industry, and government agencies. Building a strong professional network can provide valuable connections and insights in the field.
Apply for Research Positions: Explore research opportunities in academic institutions, industry R&D centers, government research agencies, or national laboratories. Look for open positions, fellowship programs, or research grants that align with your research interests. Tailor your application materials, including your resume, research statement, and recommendation letters, to highlight your research experience and skills.
Continuous Learning: Stay abreast of the latest advancements, publications, and research trends in your field. Continue to expand your knowledge, pursue professional development opportunities, and engage in lifelong learning. Attend workshops, take online courses, or pursue certifications to enhance your expertise and stay competitive in the rapidly evolving field of computer and information research.

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Computer or Information Research Scientist

Computer and information research scientists design innovative uses for new and existing technology. They study and solve complex problems in computing for business, science, medicine, and other fields.

Computer and information research scientists typically do the following:

Explore problems in computing and develop theories and models to address those problems
Collaborate with scientists and engineers to solve complex computing problems
Determine computing needs and system requirements
Develop new computing languages, software systems, and other tools to improve how people work with computers
Design and conduct experiments to test the operation of software systems, frequently using techniques from data science and machine learning
Analyze the results of their experiments
Write papers for publication and present research findings at conferences

Computer and information research scientists create and improve computer software and hardware.

To create and improve software, computer and information research scientists work with algorithms: sets of instructions that tell a computer what to do. Some difficult computing tasks require complex algorithms, which these scientists simplify to make computer systems as efficient as possible. These simplified algorithms may lead to advancements in many types of technology, such as machine learning systems and cloud computing.

To improve computer hardware, these scientists design computer architecture. Their work may result in increased efficiencies, such as better networking technology, faster computing speeds, and improved information security.

The following are examples of specialties for computer and information research scientists:

Programming. Some computer and information research scientists study and design new programming languages that are used to write software. New languages make software writing efficient by improving an existing language, such as Java, or by simplifying a specific aspect of programming, such as image processing.

Robotics . These scientists study the development and application of robots. They explore how a machine can interact with the physical world. For example, they may create systems that control the robots or design robots to have features such as information processing or sensory feedback.

Some computer and information research scientists work on multidisciplinary projects with electrical engineers, computer hardware engineers, and other specialists. For example, robotics specialists and engineers who design robots’ hardware may team up to test whether the robots complete tasks as intended.

Computer and information research scientists held about 33,500 jobs in 2021. The largest employers of computer and information research scientists were as follows:

Some scientists collaborate with engineers or other specialists or research scientists in different locations and do much of their work online.

Work Schedules

Most computer and information research scientists work full time.

Computer and information research scientists typically need at least a master’s degree in computer science or a related field. In the federal government, a bachelor’s degree may be sufficient for some jobs.

Computer and information research scientists typically need a master’s or higher degree in computer science or a related field, such as computer engineering. A master’s degree usually requires 2 to 3 years of study after earning a bachelor’s degree in a computer-related field, such as computer science or information systems. Some employers prefer to hire candidates who have a Ph.D. Others, such as the federal government, may hire candidates who have a bachelor’s degree in computer and information technology.

Computer and information research scientists who work in a specialized field may need knowledge of that field. For example, those working on biomedical applications may need to have studied biology.

Advancement

Some computer and information research scientists advance to become computer and information systems managers.

Computer and information research scientists typically have an interest in the Building, Thinking and Creating interest areas, according to the Holland Code framework. The Building interest area indicates a focus on working with tools and machines, and making or fixing practical things. The Thinking interest area indicates a focus on researching, investigating, and increasing the understanding of natural laws. The Creating interest area indicates a focus on being original and imaginative, and working with artistic media.

If you are not sure whether you have a Building or Thinking or Creating interest which might fit with a career as a computer and information research scientist, you can take a career test to measure your interests.

Computer and information research scientists should also possess the following specific qualities:

Analytical skills. Computer and information research scientists must be organized in their thinking and analyze the results of their research to formulate conclusions.

Communication skills. Computer and information research scientists must communicate well with programmers and managers and be able to clearly explain their conclusions to people with no technical background. They often write for academic journals and similar publications.

Critical-thinking skills. Computer and information research scientists work on many complex problems.

Detail oriented. Computer and information research scientists must pay close attention to their work, because a small error can cause an entire project to fail.

Ingenuity. Computer and information research scientists must continually come up with innovative ways to solve problems, particularly when their ideas do not initially work as intended.

Logical thinking . Computer algorithms rely on logic. Computer and information research scientists must have a talent for reasoning.

Math skills. Computer and information research scientists must have knowledge of advanced math and other technical topics that are critical in computing.

The median annual wage for computer and information research scientists was $131,490 in May 2021. The median wage is the wage at which half the workers in an occupation earned more than that amount and half earned less. The lowest 10 percent earned less than $74,210, and the highest 10 percent earned more than $208,000.

In May 2021, the median annual wages for computer and information research scientists in the top industries in which they worked were as follows:

Employment of computer and information research scientists is projected to grow 21 percent from 2021 to 2031, much faster than the average for all occupations.

About 3,300 openings for computer and information research scientists are projected each year, on average, over the decade. Many of those openings are expected to result from the need to replace workers who transfer to different occupations or exit the labor force, such as to retire.

The research and development conducted by computer and information research scientists turn ideas into technology. As demand for new and better technology grows, demand for computer and information research scientists will grow as well.

Rapid growth in data collection by businesses will lead to an increased need for data-mining services. Computer and information research scientists will be needed to write algorithms that help businesses make sense of very large amounts of data.

A growing emphasis on cybersecurity also should lead to new jobs because computer and information research scientists will be needed to find innovative ways to prevent potential cyberattacks. In addition, an increase in demand for software may increase the need for computer and information research scientists who create new programming languages to make software writing more efficient.

For more information about computer and information research scientists, visit

Association for Computing Machinery

Computing Research Association

IEEE Computer Society

For information about opportunities for women pursuing information technology careers, visit

National Center for Women & Information Technology

To find job openings for computer and information research scientists in the federal government, visit

Where does this information come from?

The career information above is taken from the Bureau of Labor Statistics Occupational Outlook Handbook . This excellent resource for occupational data is published by the U.S. Department of Labor every two years. Truity periodically updates our site with information from the BLS database.

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I think I have found an error or inaccurate information on this page. Who should I contact?

This information is taken directly from the Occupational Outlook Handbook published by the US Bureau of Labor Statistics. Truity does not editorialize the information, including changing information that our readers believe is inaccurate, because we consider the BLS to be the authority on occupational information. However, if you would like to correct a typo or other technical error, you can reach us at [email protected] .

I am not sure if this career is right for me. How can I decide?

There are many excellent tools available that will allow you to measure your interests, profile your personality, and match these traits with appropriate careers. On this site, you can take the Career Personality Profiler assessment, the Holland Code assessment, or the Photo Career Quiz .

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What do computer and information research scientists do , steps to become computer and information research scientist , computer and information research scientist salary , computer and information research scientist skills, computer and information research scientists career path , job outlook, frequently asked questions, conclusion , how to become a computer and information research scientist.

Career paths in computer science can go in many different directions. The role of a computer and information research scientist is one of them. It may be less known than the typical computer programming or software engineering jobs. But it comes with the opportunities of great pay and benefits.

If you want to break into high-demand computer science careers , are interested in a research-oriented job, and would love to work with algorithms, consider becoming a computer and information research scientist.

Whether you are just starting your journey in the professional world or want to pivot to a new career, here is all you need to know about how to become a computer and information research scientist.

Find More Computer Courses to Shape Your Career.

Computer and information research scientists work to improve and create new computer software and hardware. Let us look at the job description of a computer and information research scientist.

A computer and information research scientist is expected to explore fundamental issues in computing. They develop models and theories that help address these issues. They also work closely with other scientists and engineers to solve complex computing problems.

It is often the computer and information research scientists that invented new computing languages, methods and tools. They create. They create software systems, design experiments to test the operation of these systems, and analyze the result of their experiments.

Research scientists publish their findings in academic journals and present them at seminars and conferences. Computer and information research scientists design new computer architectures and algorithms that improve the performance and efficiency of computer hardware.

Becoming a computer and information research scientist is a long process. It takes an education that focuses on computer science. It is great if you are inclined towards computer science and its core aspects. But that alone does not suffice. It is a path that requires dedication, hard work and keen intelligence. Being a researcher requires an eye for detail, imagination and a research mentality. Let us look at a step-by-step process of how to become a computer and information research scientist.

Step 1: Identifying a Passion for Computers

You may be inclined to computers, their inner workings, programming languages or coding from a young age. Having a passion for a particular stream, identifying it and honing your abilities in that area can help as you are on the verge of launching your career. If you are still someone with such interests, you can cultivate them by learning new computer languages, joining clubs focusing on computer systems, extensive reading etc. You can also hone your research skills by learning on your own through various online resources.

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Step 2: Education

Starting a computer and information research career can only be backed by a solid education track record. You will need to pour in hard work and persistence.

You will need an undergraduate degree with computer science or a related subject as a core. Your post-graduate degree should also be a computer-related subject. On the whole, you should have a very good base of the fundamentals of computer systems, programming, machine learning, statistics, predictive modeling etc.

You can choose a master's program like Simplilearn’s Data Scientist masters program , developed in collaboration with IBM. It is designed to make students ready for research-centric roles in the industry. Some employers also look for a PhD in the relevant area.

Step 3: Be Industry-Ready with Certifications

Employers today look for certification in candidates as a show of skills. Leading companies like Dell, Microsoft, IBM, and SAS. These prove that you have received training from industry experts.

Before you begin a career as a computer and information scientist or attend an interview, you need to be aware of the pay scale and the average pay at different levels.

Here we take a look at Computer and information research scientists' salaries. These are from verified sources like the Bureau of Labor Statistics, the U.S Department of Labor and other international survey groups like Payscale that compile data from individuals online. Take a look!

Median annual wage as of May 2021is $131,490
The annual wage of the lowest 10% is $74,210
The highest 10% earned more than $208,000

The major industries they worked in include computer systems designs and related services, software publishers, and research and development in engineering, physical and life science. Other departments include the Federal government, colleges, universities, and professional schools.

Compared to the US salary scale, the Indian salary scales fares thus:

The average annual computer and information research scientist salary with less than one year of experience is ₹606,782
The average salary of a computer scientist with 1-4 years of experience is ₹1,448,276
The average salary of a mid-career computer scientist who has 5-9 years of experience is ₹2,367,920
The average salary of a computer scientist with 10-19 years of experience is ₹3,008,649

An aspiring computer and information research scientist should have a strong knowledge of the core aspects of computer systems like programming languages, coding, software development, technical writing, etc. Apart from these, as a computer scientist, here are some skills you should ensure you have in your arsenal.

Technical and mathematical Skills : Skills like software development, hardware engineering, computer programming, and strong knowledge of mathematics, including discrete mathematics, calculus, statistics, linear algebra etc.
Communication skills: This is a must-have when working in a collaborative environment, especially to explain their research to a technical and non-technical audience.
Technical writing skills: Many scientists require this skill for their work. Creating technical manuals, documenting project data etc., for others, especially in a comprehensive and if needed, non-technical way.
Project management skills: Scientists often have to lead IT teams for different projects. Skills like strategy, delegating tasks, allocating budgets, anticipating outcomes etc are important to carry out projects successfully.
Analytical skills: A computer scientist must have sharp analytical skills to complete various data-driven tasks. They would have to collect, test, evaluate and document data as part of their work.
Problem-solving skills : Having a logical approach and being systematic all account for the process of problem-solving. These skills are important when trying to achieve business objectives.

The Computer and Information Research Scientists Career Path can be unique for every person. How a person gets there depends on each one’s journey. However, the basics are almost the same.

For a job role as a computer and information research scientist, one would require a bachelor's in computer science. Graduating from a reputed university adds to the advantage as you get as much exposure and quality in the training you receive. You can then pursue post-graduation in a computer-related field like data science, machine learning etc. Being picky about your major during post-graduation determines a lot of your career path too.

If you are into research, you can pursue a PhD from a reputed university. You can follow your work with your research findings or find a job in a company that is looking for computer and information research scientist roles.

You may be assigned an assistant role before being promoted to associate positions.

The Bureau of Labor Statistics of the US predicts that there will be a 16% growth rate for computer scientists' job roles by 2028. This means there will be an increase in the current number of 31,700 to 37,000. This is triple the national job market growth rate during the same period. The increased data collection and the need for more experts to create processes and programs means increasing demand for computer scientists. Another reason for the rapid growth prediction is the development of cyber security and new software.

However, the largest growth will be in computer systems design and related jobs, where there are an estimated 2,800 new jobs. There is also a significant increase in the Research and development services job roles.

1. How do I become a computer scientist?

You can become a computer scientist by doing a bachelor's, master's and PhD in computer-related fields and applying for research roles in research-oriented companies.

2. How do I become an information technology researcher?

You can become an information technology researcher by pursuing your bachelor, master's and doctorate in computer-related fields. You can then apply for research roles to become an IT researcher.

3. How many years does IT take to become a computer scientist?

There is no dedicated timeline for becoming a computer scientist. You can become a computer scientist after completing your PhD and then applying for research roles.

4. How many hours do computer and information research scientists work?

The number of hours is subjective to the company, project and the complexity of a scientist's work.

5. Where do information scientists work?

They work in an organization that is research-oriented and developing new technology.

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The prospects of a computer and information research scientist are vast and rewarding. If this guide has convinced you of the opportunities waiting for you, we strongly suggest you start your journey immediately. Explore, to know more about computer courses .

If you have a bachelor's degree, one of the best ways to move forward is to get a master's degree that will propel you to the world of computer research. At Simplilearn, we offer a stellar chance of doing so with our Data Scientist Master’s Program , which is designed in collaboration with IBM. We provide the world-class training and skill required to become successful in the industry. Sign up with us to enroll now!

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Computer and Information Research Scientists: Jobs, Career, Salary and Education Information

Computer and Information Research Scientists

Career, salary and education information.

What They Do : Computer and information research scientists invent and design new approaches to computing technology and find innovative uses for existing technology.

Work Environment : Most computer and information research scientists work full time. Some work more than 40 hours per week.

How to Become One : Most jobs for computer and information research scientists require a master’s degree in computer science or a related field. In the federal government, a bachelor’s degree may be sufficient for some jobs.

Salary : The median annual wage for computer and information research scientists is $131,490.

Job Outlook : Employment of computer and information research scientists is projected to grow 21 percent over the next ten years, much faster than the average for all occupations.

Related Careers : Compare the job duties, education, job growth, and pay of computer and information research scientists with similar occupations.

Following is everything you need to know about a career as a computer or information research scientist with lots of details. As a first step, take a look at some of the following jobs, which are real jobs with real employers. You will be able to see the very real job career requirements for employers who are actively hiring. The link will open in a new tab so that you can come back to this page to continue reading about the career:

Top 3 Computer Scientist Jobs

AP Computer Science A Preference working time: (PST) * 7:00 am ~ 10:00 am; * 8:00 pm ~ 11:00 pm; Qualifications and Requirements : * Bachelor's degree in the relevant subject area; Masters or Ph.D ...

As a Computer Science Teacher, you will collaborate with teachers to create lesson plans and integrate the core curriculum into computer science projects. As you guide students through our exciting ...

Computer Science Teacher (Part Time) General Responsibilities: Under the supervision of the Director of Educational Development, plans and facilitates collaborative coding instructional sessions ...

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Top 3 Information Research Scientist Jobs

Research Scientist Job statement: The Research Scientist 's role is to develop novel molecular ... Identify and synthesize key information from internal and external knowledge bases to take charge ...

For more information , visit Follow Allergan Aesthetics on LinkedIn. Job Description The Neurotoxin Research Group at AbbVie seeks an accomplished scientist and leader. The Director/Senior Principal ...

... Research Scientist to join our RNA team. This position will play a pivotal role in the development ... information , citizenship status, uniformed service member or veteran status, or any other ...

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What Computer and Information Research Scientists Do [ About this section ] [ To Top ]

Computer and information research scientists invent and design new approaches to computing technology and find innovative uses for existing technology. They study and solve complex problems in computing for business, science, medicine, and other fields.

Duties of Computer and Information Research Scientists

Computer and information research scientists typically do the following:

Explore fundamental issues in computing and develop theories and models to address those issues
Help scientists and engineers solve complex computing problems
Invent new computing languages, tools, and methods to improve the way in which people work with computers
Develop and improve the software systems that form the basis of the modern computing experience
Design experiments to test the operation of these software systems
Analyze the results of their experiments
Publish their findings in academic journals and present their findings at conferences

Computer and information research scientists create and improve computer software and hardware.

Creating and improving software involves working with algorithms, which are sets of instructions that tell a computer what to do. Some computing tasks are very difficult and require complex algorithms. Computer and information research scientists try to simplify these algorithms to make computer systems as efficient as possible. The algorithms allow advancements in many types of technology, such as machine learning systems and cloud computing.

Computer and information research scientists design new computer architecture that improves the performance and efficiency of computer hardware. Their work often leads to technological advancements and efficiencies, such as better networking technology, faster computing speeds, and improved information security. In general, computer and information research scientists work at a more theoretical level than do other computer professionals.

Some computer scientists work with electrical engineers , computer hardware engineers , and other specialists on multidisciplinary projects. The following are examples of types of specialties for computer and information research scientists:

Data science. Computer and information research scientists write algorithms that are used to detect and analyze patterns in very large datasets. They improve ways to sort, manage, and display data. Computer scientists build algorithms into software packages that make the data easier for analysts to use. For example, they may create an algorithm to analyze a very large set of medical data in order to find new ways to treat diseases. They may also look for patterns in traffic data to help clear accidents faster.

Robotics . Some computer and information research scientists study how to improve robots. Robotics explores how a machine can interact with the physical world. Computer and information research scientists create the programs that control the robots. They work closely with engineers who focus on the hardware design of robots. Together, these workers test how well the robots do the tasks they were created to do, such as assemble cars or collect data on other planets.

Programming . Computer and information research scientists design new programming languages that are used to write software. The new languages make software writing more efficient by improving an existing language, such as Java, or by making a specific aspect of programming, such as image processing, easier.

Work Environment for Computer and Information Research Scientists [ About this section ] [ To Top ]

Computer and information research scientists hold about 33,500 jobs. The largest employers of computer and information research scientists are as follows:

Some scientists collaborate with engineers or other specialists or research scientists in different locations and do much of their work online.

Computer and Information Research Scientist Work Schedules

Most computer and information research scientists work full time.

How to Become a Computer or Information Research Scientist [ About this section ] [ To Top ]

Get the education you need: Find schools for Computer and Information Research Scientists near you!

Most jobs for computer and information research scientists require a master's degree in computer science or a related field. In the federal government, a bachelor's degree may be sufficient for some jobs.

Education for Computer and Information Research Scientists

Most computer and information research scientists need a master's degree in computer science or a related field, such as computer engineering. A master's degree usually requires 2 to 3 years of study after earning a bachelor's degree in a computer-related field, such as computer science or information systems.

Computer scientists who work in a specialized field may need knowledge of that field. For example, those working on biomedical applications may need to have taken some biology classes.

Advancement for Computer and Information Research Scientists

Some computer scientists may become computer and information systems managers .

Important Qualities for Computer and Information Research Scientists

Analytical skills. Computer and information research scientists must be organized in their thinking and analyze the results of their research to formulate conclusions.

Critical-thinking skills. Computer and information research scientists work on many complex problems.

Detail oriented. Computer and information research scientists must pay close attention to their work, because a small programming error can cause an entire project to fail.

Ingenuity. Computer and information research scientists must continually come up with innovative ways to solve problems, particularly when their ideas do not initially work as intended.

Logical thinking. Computer algorithms rely on logic. Computer and information research scientists must have a talent for reasoning.

Math skills. Computer and information research scientists must have knowledge of advanced math and other technical topics that are critical in computing.

Computer and Information Research Scientist Salaries [ About this section ] [ More salary/earnings info ] [ To Top ]

The median annual wage for computer and information research scientists is $131,490. The median wage is the wage at which half the workers in an occupation earned more than that amount and half earned less. The lowest 10 percent earned less than $74,210, and the highest 10 percent earned more than $208,000.

The median annual wages for computer and information research scientists in the top industries in which they work are as follows:

Job Outlook for Computer and Information Research Scientists [ About this section ] [ To Top ]

Employment of computer and information research scientists is projected to grow 21 percent over the next ten years, much faster than the average for all occupations.

Employment of Computer and Information Research Scientists

Careers Related to Computer and Information Research Scientists [ About this section ] [ To Top ]

Computer and information systems managers.

Computer and information systems managers, often called information technology (IT) managers or IT project managers, plan, coordinate, and direct computer-related activities in an organization. They help determine the information technology goals of an organization and are responsible for implementing computer systems to meet those goals.

Computer Hardware Engineers

Computer hardware engineers research, design, develop, and test computer systems and components such as processors, circuit boards, memory devices, networks, and routers.

Computer Network Architects

Computer network architects design and build data communication networks, including local area networks (LANs), wide area networks (WANs), and Intranets. These networks range from small connections between two offices to next-generation networking capabilities such as a cloud infrastructure that serves multiple customers.

Computer Programmers

Computer programmers write and test code that allows computer applications and software programs to function properly. They turn the program designs created by software developers and engineers into instructions that a computer can follow.

Computer Systems Analysts

Computer systems analysts, sometimes called systems architects, study an organization's current computer systems and procedures, and design solutions to help the organization operate more efficiently and effectively. They bring business and information technology (IT) together by understanding the needs and limitations of both.

Database Administrators

Database administrators (DBAs) use specialized software to store and organize data, such as financial information and customer shipping records. They make sure that data are available to users and secure from unauthorized access.

Data Scientists

Data scientists use analytical tools and techniques to extract meaningful insights from data.

Information Security Analysts

Information security analysts plan and carry out security measures to protect an organization's computer networks and systems. Their responsibilities are continually expanding as the number of cyberattacks increases.

Network and Computer Systems Administrators

Computer networks are critical parts of almost every organization. Network and computer systems administrators are responsible for the day-to-day operation of these networks.

Software Developers

Software developers are the creative minds behind computer programs. Some develop the applications that allow people to do specific tasks on a computer or another device. Others develop the underlying systems that run the devices or that control networks.

Web Developers

Web developers design and create websites. They are responsible for the look of the site. They are also responsible for the site's technical aspects, such as its performance and capacity, which are measures of a website's speed and how much traffic the site can handle. In addition, web developers may create content for the site.

Top Executives

Top executives devise strategies and policies to ensure that an organization meets its goals. They plan, direct, and coordinate operational activities of companies and organizations.

More Computer and Information Research Scientist Information [ About this section ] [ To Top ]

For more information about computer and information research scientists, visit

Association for Computing Machinery

IEEE Computer Society

For information about opportunities for women pursuing information technology careers, visit

National Center for Women & Information Technology

A portion of the information on this page is used by permission of the U.S. Department of Labor.

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In 1965, Intel co-founder Gordon Moore wrote a short article for Electronics magazine in which he stated his belief that processor capabilities were doubling every year. He revised his statement 10 years later, saying he believed processors would double in complexity every other year as a result of continually emerging technologies and the physical properties of computer chips and their components. That belief quickly became known as “Moore’s Law,” which simply says computers will double in performance capability every two years.

The industry consensus is that Moore’s law won’t persist beyond the 2020s, as the trend of shrinking transistors means they would eventually have to be smaller than individual molecules, which isn’t a real possibility in the near future. However, that doesn’t mean there won’t be more advancements in computing technology. It’s up to the next generation of computer science experts to innovate and improve computers through programming, networking, materials, and research. These experts, often known as computer and information research scientists, work in many different industries, from biomedical engineering to sports analytics. Continue reading to learn more about how to become a computer and information research scientist, as well as the projected market and salary for this in-demand career.

Computer scientists working on computer hardware

What Does a Computer and Information Research Scientist Do?

Computer and information research scientists advance the field of computing technology through research and experimentation. As experts in how computers and network systems operate, they come up with new ways to program, assemble, and link computers and other devices. Their work improves processing, data transfer speeds, and more. They design experiments to test theories about new algorithms, programs, or systems and write research papers to be published in academic journals. They often work in data science, managing and protecting large data sets for governments or corporations. They may also work in computer system design or engineering firms, helping develop new software, systems, or programming languages.

Steps for Becoming a Computer and Information Research Scientist

Becoming a computer and information research scientist takes more than an interest in the inner workings of computers. It requires years of study, an advanced education, and an intricate knowledge of computer networks. Along the way, in the classroom and beyond, these tech experts pick up extensive experience working with computers in many different capacities.

Dive Into Computers

The most basic requirement for computer and information research scientists is a passion for computers. Even before getting out of high school, those interested in computer and information research can start to learn basic computer programming languages and functions, participating in school and extracurricular clubs where they might create basic software or build desktop computer systems. YouTube tutorials and other online learning materials also allow aspiring computer and information research scientists to work toward their goals independently.

Get the Right Education

Computer and information research scientists hold advanced degrees in their field. Their postsecondary educational path starts with a computer-related degree, such as a bachelor’s in data science or computer science. These programs teach important skills in programming, statistics, machine learning, and predictive modeling. To become a computer and information research scientist, aspiring professionals also need to complete a postgraduate degree, such as Maryville University’s online Master’s in Data Science . In this program, students build on their undergraduate education with courses in data mining, big data analytics, deep learning, and experimental design. Courses at an advanced level take skills earned in a bachelor’s degree program to the next level. At Maryville University, for example, master’s in data science students learn how to conduct the research and data analysis necessary to become a scientist in this field.

Earn Certifications

Many of the world’s top technology and computing corporations have their own industry certifications, which data scientists can earn to illustrate their capabilities to employers. Dell, IBM, Microsoft, and SAS offer some of the more popular ones.

Computer and Information Research Scientist Salaries

The U.S. Bureau of Labor Statistics (BLS) reports the median annual salary for computer and information research scientists was $118,370 per year as of May 2018, while the top 10% earned approximately $183,820 annually. The highest-paying industry by median annual salary was software publishing ($140,220), followed by research in the physical, engineering, and life sciences ($128,570) and computer systems design and related services ($124,220).

Employment Outlook for Computer and Information Research Scientists

As of May 2018, according to the BLS, there were 31,700 computer and information research scientist jobs in the United States. The BLS expects that number to reach 37,000 jobs by 2028 — a 16% growth rate, which is more than three times the national job market growth rate during the same period. The largest area of growth will be in computer systems design and related jobs, with 2,800 of the 5,200 new jobs added in that area. Scientific research and development services (1,200 jobs) will also see significant growth.

Learn More About How to Become a Computer and Information Research Scientist

Computer experts who want to take their knowledge of hardware, software, and programming to the next level should consider pursuing the education, experience, and certification required to become a computer and information research scientist. The field is growing, and innovators are needed to meet the demand for development in many industries. Discover how Maryville University’s online Master’s in Data Science can help you take the next step.

Research Scientist Skills

Learn about the skills that will be most essential for Research Scientists in 2024.

Getting Started as a Research Scientist

What is a Research Scientist
How To Become
Certifications
Tools & Software
LinkedIn Guide
Interview Questions
Work-Life Balance
Professional Goals
Resume Examples
Cover Letter Examples

What Skills Does a Research Scientist Need?

Find the important skills for any job.

Types of Skills for Research Scientists

Critical thinking and problem-solving, technical proficiency and specialization, data analysis and computational skills, communication and dissemination, project management and organization, top hard skills for research scientists.

Empowering discovery through robust data analysis, cutting-edge experimentation, and interdisciplinary expertise in today's dynamic scientific landscape.

Statistical Analysis and Modeling
Experimental Design and Execution
Data Mining and Machine Learning
Scientific Writing and Publishing
Advanced Mathematics
Laboratory Techniques and Instrumentation
Computer Programming and Simulation
Big Data Analytics
Research Project Management
Domain-Specific Knowledge (e.g., Genomics, Neuroscience, Materials Science)

Top Soft Skills for Research Scientists

Fostering innovation through critical thinking, collaboration, and resilience, while leading with emotional intelligence and meticulous organization.

Critical Thinking and Problem Solving
Effective Communication
Collaboration and Teamwork
Adaptability and Flexibility
Creativity and Innovation
Time Management and Organization
Attention to Detail
Resilience and Perseverance
Emotional Intelligence
Leadership and Mentoring

Most Important Research Scientist Skills in 2024

Interdisciplinary collaboration, advanced data analysis and interpretation, scientific communication and public engagement, grant writing and fundraising acumen, problem-solving and critical thinking, technical proficiency in emerging technologies, project management and organizational skills, adaptability to scientific paradigm shifts.

Show the Right Skills in Every Application

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Deepen Your Expertise with Specialized Courses: Enroll in advanced courses that focus on cutting-edge topics within your field to deepen your expertise and stay abreast of the latest scientific breakthroughs.
Master Data Analysis and Statistical Software: Become proficient in the latest data analysis tools and software, such as R, Python, or specialized bioinformatics software, to enhance your research capabilities.
Collaborate on Interdisciplinary Research Projects: Seek out opportunities to work with professionals from different scientific disciplines to broaden your perspective and foster innovation through cross-pollination of ideas.
Participate in Scientific Conferences and Seminars: Attend and, if possible, present your research at national and international conferences to stay informed about recent developments and network with leading scientists.
Contribute to Peer-Reviewed Journals: Writing and reviewing articles for reputable scientific journals will not only contribute to your field but also refine your critical thinking and writing skills.
Engage with Research Funding and Grant Writing: Develop your skills in writing grant proposals to secure funding for your research, which is a critical component of a successful scientific career.
Adopt Open Science Practices: Embrace open science by sharing your data and findings openly when possible, and using open-source resources to promote transparency and reproducibility in research.
Develop Teaching and Mentoring Skills: Take on roles that involve teaching or mentoring to improve your communication skills and give back to the scientific community by helping to train the next generation of researchers.
Stay Informed on Ethical Research Practices: Ensure that you are up-to-date with the ethical considerations and regulations in your field to conduct responsible and credible research.
Invest in Soft Skills Development: Enhance your soft skills, such as teamwork, leadership, and problem-solving, which are invaluable in collaborative research environments and when leading projects or labs.

Skill FAQs for Research Scientists

What are the emerging skills for research scientists today, how can research scientists effectivley develop their soft skills, how important is technical expertise for research scientists.

Research Scientist Education

More Skills for Related Roles

Unearthing insights from data, driving strategic decisions with predictive analytics

Unlocking business insights through data, driving strategic decisions with numbers

Unearthing insights and data to drive decision-making, shaping the future of research

Driving innovation through data, transforming industries with machine learning insights

Transforming raw data into valuable insights, fueling business decisions and strategy

Transforming data into actionable insights, driving business decisions and growth

Start Your Research Scientist Career with Teal

How to Become a Computer and Information Research Scientist

Are you interested in a career as a computer and information research scientist? Here are the steps you can take to pursue this profession.

Do you think of ways to improve your computer's capacity and develop new and improved ways to process and store information? Then it would be best if you considered a career as a computer and information research scientist.

Computer and information research scientists look for new ideas, solutions, and applications that enhance computer functions and improve information security. Read on to learn how this profession contributes to science, technology, and business development and how you can build a career in this lucrative field.

Who Are Computer and Information Research Scientists, and What Do They Do?

A computer and information research scientist, also known as a computer research scientist, is a computer professional who simplifies and improves computer algorithms to increase the system's efficiency. These improved algorithms set the foundation for technological advancements in machine learning, cloud computing, and the like.

Furthermore, computer and information research scientists find limitations in computation and develop solutions and models that address them. Thus, they help engineers solve complex computing tasks and create new and improved computing languages, tools, and processes that simplify how people work with computers.

In addition, the discipline involves advanced theoretical knowledge. Finally, computer and information research scientists conduct experiments to test the functionality of developed systems, analyze experimental results, and publish their observations in academic journals for future reference.

Becoming a computer and information research scientist typically requires you to learn the theoretical aspects of the profession and develop the required technical and soft skills. On that note, here is how to get the required knowledge, skill set, and experience to stand out as a computer and information research scientist.

1. Get a Degree in Computer Science or a Related Field

Computer and information science is a field that requires a deep understanding of the theories of computing and data processing. Therefore, getting a computer science/engineering degree or any related field is the first step.

It would be best to go for something higher than a college degree. You can go further by taking a master's or advanced degree in, preferably, computer science. That way, you get well-grounded in the theoretical aspect of the profession. Additionally, a solid educational background will enable you to conduct periodic research with ease.

2. Choose a Specialty

Computer and information research science is a broad discipline with branches and applications that extend to other sectors of the information and technology industry. Consequently, you can find a niche that interests and suits you.

As a computer and information research scientist, you can specialize in studying hardware architecture and researching new ways of designing computer chips and processors that enhance computing power. Or, if software development is your thing, you can specialize in writing software for computers or electronic components of various machines.

In addition, some computer and information research scientists focus on AI development. They research ways to improve how machines and robots process data and function for increased efficiency and optimal performance. Also, they work together with hardware and software engineers to design and test each system to ensure they function as required.

3. Learn the Required Technical Skills

As with any other tech profession, you must build relevant tech skills to succeed as a computer and information research scientist. For instance, tech skills like programming are a must-have in the industry.

Furthermore, it would help if you had an idea of cloud computing and how it impacts the capacity of computer systems. Additionally, you should be familiar with major data analytics tools, like Microsoft Excel, to record and analyze data and have a solid background in cybersecurity. Here are some cybersecurity online courses to start with .

4. Develop the Necessary Soft Skills

As a computer and information research scientist, your job requires you to possess soft skills that will help you work in teams and succeed in your career. One vital skill to have is critical and analytical thinking, which enables you to examine projects, find shortfalls in the system, and brainstorm solutions to complex challenges.

Also, you should command excellent communication skills and teamwork to help you communicate your ideas articulately and work effectively with other professionals. Soft skills are in demand in the industry and are necessary for a successful career.

5. Build Your Portfolio

After getting the required education and developing the relevant skillset, start building a portfolio where you document the projects you undertake and your problem-solving approach. It's important to note that a quality portfolio can open doors to employment for you. Hence, it would be best to spend time working on relevant projects to add to your portfolio.

Further, a strong portfolio indicates your experience level, which employers look out for when hiring candidates. As a newbie in the profession, you can take on personal projects, like researching and developing models that improve computing power, to build your portfolio.

6. Write a Technical Resume

A well-written resume could be your one-way ticket to that dream job. Therefore, you should craft a solid resume that best describes your professional capacity, so you can confidently apply for roles in the field. Here is how to write a tech resume .

Your resume should include your educational background, soft and technical skills, and experience in the industry. You can add personal projects to the list and update your resume as you gain more hands-on experience. Additionally, ensure to tailor your resume according to your specialization and employers' needs.

7. Apply for Related Roles to Gain Experience

Now, you are ready to take on roles in the industry and gain industrial experience. As a computer and information research scientist, there are many job opportunities you can apply for across several industries.

Most computer and information research scientists work for software development companies, research and development institutions, tech firms, and even government agencies. Furthermore, you can go into full-time or part-time teaching.

Whatever option you choose to work as a computer and information research scientist, rest assured the profession has great prospects for career development.

Start a Career in Computer and Information Research Science Easily

Increasing computer and related technology applications like AI and machine learning have resulted in a corresponding demand for improved computing power and functionality.

Becoming a computer and information research scientist allows you the flexibility to contribute to technological advancements in various fields, like software development, cloud computing, and AI.

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How to Become a Computer Scientist

By Ajoke Aminu

Published: March 6, 2024

Do you dream of becoming the next Bill Gates? Well, becoming a computer scientist might just be the path for you, as we live in a world where technology is increasingly important, yet many feel overwhelmed by it and unable to understand the basics. Fortunately, this article provides easy-to-understand explanations for the fundamentals of computer science that gets you ahead in tech.

Career Summary

Computer scientist salary.

According to recent studies, the average computer scientist salary in the United States is a whopping US$94,337– not your average 9-to-5 paycheck! But wait, it gets even better as you scale:

Entry Salary (US$94k)
Median Salary (US$117k)
Executive Salary (US$164k)

To put that into perspective, the average income for a US citizen is around US$60,000 per year, meaning Computer Scientists are making almost double the average American’s salary!

What does a Computer Scientist do?

A computer scientist, for starters, is responsible for designing and implementing the software and hardware systems that power our digital world. Think of them as the superheroes of the cyberworld– the ones who ensure that your favorite apps run smoothly, your emails are delivered securely, and your devices stay free of pesky programs that threaten their functionality. From solving complex mathematical equations to debugging faulty code, computer and information research scientists are experts in all things digital.

Computer Scientist Career Progression

Entry-Level Positions: Computer scientists often begin their careers in entry-level roles such as software developer , programmer, or data analyst . These positions allow them to gain practical experience and apply their foundational knowledge.
Mid-Level Positions: After gaining a few years of experience, computer scientists can advance to mid-level positions such as software engineer, data scientist , or systems analyst. They take on more complex responsibilities, work on larger projects, and may start leading small teams.
Senior-Level Positions: With significant experience and expertise, computer scientists can move into senior-level positions like senior software architect , data science manager, or technical lead. In these roles, they have greater responsibilities, mentor junior team members, make strategic decisions, and may oversee multiple projects.
Specialization or Management Roles: As computer scientists progress in their careers, they may choose to specialize in a specific area of computer science, such as artificial intelligence, cybersecurity, or cloud computing. Alternatively, they can transition into management roles like IT project manager , technology director, or research scientist, where they oversee teams, budgets, and strategic initiatives.
Leadership or Executive Positions: With extensive experience and demonstrated leadership skills, computer scientists can advance to executive positions such as Chief Technology Officer (CTO), Chief Information Officer (CIO), or technology consultant. In these roles, they provide strategic direction, drive innovation, and make high-level decisions that impact the organization’s technology landscape.

Computer scientists are in high demand across various industries, providing a wide range of job opportunities and career advancement prospects.
Due to the demand for their skills, computer scientists often enjoy competitive salaries and attractive compensation packages.
Computer scientists have the opportunity to work on cutting-edge technologies and contribute to technological advancements, fostering innovation and creativity.
Many computer science roles offer flexible work arrangements, such as remote work options, flexible hours, and location independence, providing a better work-life balance.
Computer science is a dynamic field, requiring professionals to engage in continuous learning. This keeps their skills up-to-date and allows for ongoing growth and development.
The field of computer science evolves rapidly, requiring professionals to constantly adapt to new technologies, programming languages, and industry trends.
Computer scientists often face tight deadlines and high-pressure situations, especially when working on critical projects or dealing with complex technical challenges.
The fast-paced nature of the field and the need for technical expertise can lead to high expectations from employers and clients, requiring computer scientists to consistently perform at a high level.

Most Important Computer Scientist Skills

Programming and Coding
Network and Security
Mathematics and Algorithms
Data Structures
Software Development Methodologies

Popular Computer Scientist Specialization

Artificial Intelligence (AI) and Machine Learning: This specialty focuses on developing algorithms and models that enable computers to simulate intelligent behavior. Computer scientists in this field work on tasks like natural language processing, computer vision, robotics, and predictive modeling.
Data Science and Analytics: Data scientists specialize in extracting insights and valuable information from large datasets. They use statistical analysis, machine learning, and data visualization techniques to uncover patterns, trends, and correlations that can drive informed decision-making.
Cybersecurity: With the increasing prevalence of cyber threats, computer scientists specializing in cybersecurity play a critical role in protecting computer systems, networks, and data from unauthorized access, breaches, and other security risks. They develop security protocols, perform risk assessments, and implement measures to safeguard digital assets.
Software Engineering: Software engineers focus on designing, developing, and maintaining software systems. They apply engineering principles to create robust, scalable, and efficient software solutions for various purposes, including web and mobile applications, operating systems, and enterprise software.
Computer Networks and Systems: Computer scientists specializing in networks and systems design and maintain the infrastructure that allows computers to communicate and share resources. They work on tasks such as network architecture, network security, cloud computing, and distributed systems.

How to become a Computer Scientist

Considering a future in tech can be mind-boggling without the right guidance, especially as a computer scientist. We are here to hold you by the hands as you take the leap into the exciting world of computer science. In this guide, you will find the key steps you need to take to become the next tech superstar.

Getting a Tech Education

Is a computer science degree required.

No, you do not necessarily need a degree to become a computer scientist . Regardless, it is still relevant. While a formal degree in computer science or a related field can provide a strong foundation and open up opportunities, it is not the only path to a successful career in computer science.

So, why should I get a Computer Science degree?

Several businesses are more likely to interview candidates with a reasonable degree of education, which is highlighted even in the computer scientist job description.

Despite the possibility to succeed without a computer science degree , it is essential to consider these factors before deciding not to obtain one:

Foundational Knowledge: A degree program provides a structured curriculum that covers essential concepts, theories, and principles of computer science. It offers a comprehensive understanding of algorithms, data structures, programming languages, software development, computer architecture, and other core topics. This foundational knowledge forms a solid base for a career in computer science.
Specialized Education: A degree program allows you to specialize in specific areas of computer science based on your interests and career goals. You can choose elective courses or concentrate on fields like artificial intelligence, cybersecurity, software engineering, database systems, or computer graphics. Specialization can give you an advantage in the job market and open up opportunities in specific industries or research areas.
Credibility and Validation: A degree serves as tangible proof of your dedication, commitment, and expertise in the field. Employers often value a degree as it demonstrates that you have undergone a rigorous academic program and acquired a certain level of knowledge and skills. It can help you stand out among other candidates, especially in competitive job markets.
Career Advancement: Some roles in the field, particularly in research or academia, may require an advanced degree, such as a Master’s or Ph.D. Having a bachelor’s degree in computer science can be a stepping stone toward pursuing higher education and advancing your career in specialized areas.

What is the typical duration to earn a degree in Computer Science?

If you are wondering how long it will take before you can officially call yourself a computer scientist, the answer is not as simple as a one-size-fits-all approach.

Depending on the program you choose you should earn various degrees in the following timelines:

Bachelor’s Degree: A traditional undergraduate degree in computer science, such as a Bachelor of Science (B.S.) or a Bachelor of Arts (B.A.), typically takes around four years to complete. This duration assumes full-time enrollment and successful completion of all required courses.
Accelerated Bachelor’s Degree: Some universities offer accelerated programs that allow motivated students to complete their bachelor’s degree in a shorter timeframe, often in three years . These programs often involve heavier course loads, summer semesters, or credit for prior learning.
Master’s Degree: A Master of Science (M.S.) in computer science typically takes about two years to complete after earning a bachelor’s degree. This duration may vary depending on whether the program is pursued on a full-time or part-time basis.
Ph.D. Degree: A Doctor of Philosophy (Ph.D.) in computer science is a research-focused degree that can take anywhere from four to six years or more to complete. The duration depends on the student’s research progress, the complexity of the research topic, and other factors specific to the individual’s work.

Financial Commitments Involved in Studying Computer Science at University

Have you ever found yourself hovering over the “enroll” button for a Computer Science program, only to hesitate because you’re unsure of the costs? Although the cost of tuition for computer science programs at universities in the United States varies, this estimate can guide you.

On average, for the 2021-2022 academic year, the tuition fees for computer science degrees were approximately $13,300 for in-state students attending public universities and $46,497 for out-of-state students .

Additionally, you must remember to consider other expenses such as room and board, books and supplies, technology and equipment, and miscellaneous. To get an accurate estimate of the total cost, it’s recommended to visit the websites of specific universities you are interested in or contact their financial aid offices. Lastly, it’s also worth mentioning that computer science financial aid, scholarships, and grants can help offset the cost of studying.

Can I earn my Computer Science Degree Through Online Learning?

Yes, it is possible to become a computer scientist through online education . Some forms of online learning include:

Self-study: There are abundant online resources, tutorials , and courses available that can help you learn computer science concepts and programming languages. Platforms like Coursera and Udemy offer a wide range of courses from reputable institutions and instructors.
Bootcamps: Coding bootcamps are intensive, short-term training programs designed to teach specific programming skills. They often focus on practical application and hands-on experience, preparing students for specific roles in the industry. Bootcamps are typically shorter and more focused than traditional degrees.
Open-source contributions and projects: Engaging with open-source projects allows you to collaborate with other developers, build a portfolio, and demonstrate your skills to potential employers. Contributing to open-source projects can be a valuable learning experience and a way to showcase your abilities.
Certifications: Industry-recognized certifications, such as those offered by organizations like Microsoft , Cisco , or AWS , can demonstrate your expertise in specific areas of computer science and increase your job prospects.

Alternative Web Resources to Learn Computer Science Skills

Whether you’re a beginner looking to dip your toes into the world of computer science or a seasoned professional seeking new areas to explore, there’s no better time to start utilizing these invaluable web resources:

Codecademy : Codecademy focuses on interactive coding tutorials for different programming languages, including Python, JavaScript, HTML/CSS, and more. It provides a hands-on learning experience with real-time code editors and exercises.
FreeCodeCamp : FreeCodeCamp is an interactive platform that offers coding challenges and projects to help you learn web development and other computer science skills. It covers topics like HTML, CSS, JavaScript, and various frameworks.
Stack Overflow : Stack Overflow is a popular online community for programmers where you can ask questions, find answers, and engage in discussions related to computer science and programming. It’s a valuable resource for troubleshooting, gaining insights, and connecting with other developers.
GitHub : GitHub is a code hosting platform that also serves as a learning resource. You can explore open-source projects, collaborate with others, and contribute to existing projects to improve your coding skills and gain real-world experience.

8 Essentials Skills Needed to Become a Professional Computer Scientist

Programming: Proficiency in programming languages is fundamental for computer and information research scientists. You will learn how to write efficient and maintainable code, understand data structures and algorithms, and develop software solutions to solve problems.
Algorithm Design and Analysis: You will learn how to design and analyze algorithms, which are step-by-step procedures for solving computational problems. This skill is essential for optimizing performance, understanding efficiency, and evaluating trade-offs in algorithmic solutions.
Data Structures: Understanding data structures is crucial for organizing and manipulating data efficiently. Computer and information research scientists will learn about arrays, linked lists, stacks, queues, trees, graphs, and other data structures that facilitate effective data management and retrieval.
Software Development: Computer scientists gain expertise in software development methodologies and practices. This includes understanding the software development life cycle, version control, debugging techniques, testing strategies, and writing maintainable and scalable code. It is one of the most common skill requirements in computer scientist job description.
Computer Architecture: You will learn about computer organization and architecture, understanding the hardware components, memory systems, and how software interacts with the underlying hardware infrastructure. This knowledge is valuable for optimizing software performance.
Artificial Intelligence and Machine Learning: With the increasing influence of AI and machine learning, computer scientists often delve into these areas. You can gain skills in building and training models, data analysis, pattern recognition, and developing intelligent systems. AI is also another commonly required skill in a computer scientist job description.
Database Systems: Understanding database management systems is important for handling data storage, retrieval, and manipulation. You will learn about structured query language (SQL), relational database design, normalization, and working with database systems efficiently.
Networking and Security: Computer scientists often acquire knowledge of computer networks, network protocols, and security fundamentals. This includes understanding network architectures, protocols, encryption, and implementing measures to protect systems and data.

Practical Experience in Computer Science: Employment, Internship & Job Opportunities

Computer and information research scientists are in luck when it comes to practical experience because there are countless internship and job opportunities out there waiting for you. These chances will give you the opportunity to work on exciting projects, utilize cutting-edge technology, and develop crucial professional skills and network. Interestingly, the computer science industry is not slowing down anytime soon, so there’s no better time to jump on board and start gaining some hands-on experience.

Internship Opportunities for a Computer Scientist Across Different Niches

Software Development Internship : Many companies offer internships focused on software development, where you can work on real-world projects, collaborate with experienced developers, and gain practical coding skills. These internships may involve front-end or back-end development, mobile app development, or working with specific programming languages and frameworks.
Data Science and Analytics Internship : I nternships in data science and analytics involve working with large datasets, performing data analysis, applying machine learning techniques, and extracting insights. This can be in industries like finance, healthcare, e-commerce, or any field that relies on data-driven decision-making.
Cybersecurity Internship : With the increasing importance of cybersecurity, internships in this field provide opportunities to learn about and contribute to securing computer systems, networks, and data. You may work on tasks like vulnerability assessments, threat analysis, implementing security measures, or participating in incident response.
Artificial Intelligence and Machine Learning Internship : Internships in AI and machine learning allow you to work on projects related to natural language processing, computer vision, recommendation systems, or other AI applications. You may get hands-on experience with training models, working with data, and developing AI-based solutions.
Web Development and UI/UX Design Internship : These internships focus on designing and developing user-friendly websites, web applications, and user interfaces. You may gain experience in front-end development using HTML, CSS, JavaScript, and frameworks like React or Angular. UI/UX design internships involve creating intuitive and visually appealing user interfaces.
IT and Systems Internship : Internships in IT departments allow you to gain experience in managing computer systems, troubleshooting hardware or software issues, setting up networks, or working on infrastructure projects. This can be in organizations of various sizes, from startups to large enterprises.
Gaming and Virtual Reality Internship : Internships in the gaming industry involve game development, graphics programming, virtual reality (VR), or augmented reality (AR) projects. Computer and information research scientists may work on designing game mechanics, creating game assets, or implementing VR/AR experiences.

Top 10 High-demand Job Opportunities for Computer Science Experts

In the fast-paced world of technology, computer science experts are in high demand for roles, such as:

Software Developer/Engineer
Data Scientist/Analyst
Artificial Intelligence/Machine Learning Engineer
Cybersecurity Analyst/Engineer
Systems Analyst/Architect
Database Administrator
IT Project Manager
Research Scientist
User Experience/User Interface (UX/UI) Designer
Technical Consultant

Industries and Companies That Hire Computer Scientists

Technology Companies
Software Development Companies
IT Consulting Firms
Financial Institutions
Healthcare Organizations
Government Agencies
Research Institutions
Academic Institutions
E-commerce Companies
Entertainment Industry (gaming, animation, etc.)
Telecommunications Companies
Manufacturing Companies with a Focus on Technology
Transportation and Logistics Companies
Energy and Utility Companies
Defense and Security Organizations
Digital Marketing Agencies
Media and Broadcasting Companies

Finding a Balance in the Life of a Computer Scientist

Computer scientists typically enjoy great work arrangements with remote options, flexible hours, and location independence, promoting better personal commitment management and work-life balance. Their schedules can adapt to optimize productivity, although project demands may require additional hours during critical phases.

Essentially, finding remote work opportunities provide autonomy, reduced commuting, and increased work-life balance. The project-based nature of their work allows for breaks and downtime between milestones, supporting work-life balance. Company culture plays a role as well, with organizations prioritizing work-life balance through policies, initiatives, and a supportive environment.

Most importantly, personal time management, effective task prioritization, and setting boundaries contribute to maintaining balance, while continuous learning and skill development strike a harmony between work-related and personal interests, fostering a well-rounded lifestyle.

What’s the Career Outlook for Computer Scientist?

With the rapid advancement of technology and digital transformation across industries, there is a consistently high demand for skilled computer and information research scientists. Computer and information research scientists can anticipate a 21% increase from 2021 to 2031, which is higher compared to the average percentage of other professions.

Thus, there will be approximately 3,300 computer and information research scientists job openings per year over the next decade. The competitive computer scientist salary, entrepreneurial prospects, and global demand make computer science an attractive field. Overall, the career outlook for computer scientists is promising, with ample opportunities for growth, innovation, and contribution to society.

Computer Scientist Popular Career Specialties

Should I become a Computer Scientist?

Deciding whether to become a computer scientist is not a trivial matter and requires careful consideration of many factors. After reading this article, you now have a better idea of what the field entails, what skills you need, and what opportunities you can pursue. But don’t let the facts alone sway your decision.

Remember that your personal interests, passions, and strengths should also come into play. Are you a problem solver at heart? Do you enjoy learning new technologies and tools? Do you like working in teams or on your own? These are some of the questions you should ask yourself before committing to a career in computer science.

Once you’ve made up your mind, keep in mind that your long-term goals and aspirations can help you navigate the ever-changing landscape of the tech industry. Whether you want to start your own business, work for a non-profit, or pursue a Ph.D., the knowledge and skills you acquire as a computer scientist can open up many doors and opportunities. So, be confident and stay curious!

Careers Related to Computer Scientist

Computer Programmer
Data Analyst
Information Technology Manager
Network Architect
Software Developer

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Machine Learning & Data Science Foundations

Online Graduate Certificate

Be a Game Changer

Harness the power of big data with skills in machine learning and data science, your pathway to the ai workforce.

Organizations know how important data is, but they don’t always know what to do with the volume of data they have collected. That’s why Carnegie Mellon University designed the online Graduate Certificate in Machine Learning & Data Science Foundations; to teach technically-savvy professionals how to leverage AI and machine learning technology for harnessing the power of large scale data systems.

Computer-Science Based Data Analytics

When you enroll in this program, you will learn foundational skills in computer programming, machine learning, and data science that will allow you to leverage data science in various industries including business, education, environment, defense, policy and health care. This unique combination of expertise will give you the ability to turn raw data into usable information that you can apply within your organization.

Throughout the coursework, you will:

Practice mathematical and computational concepts used in machine learning, including probability, linear algebra, multivariate differential calculus, algorithm analysis, and dynamic programming.
Learn how to approach and solve large-scale data science problems.
Acquire foundational skills in solution design, analytic algorithms, interactive analysis, and visualization techniques for data analysis.

An online Graduate Certificate in Machine Learning & Data Science from Carnegie Mellon will expand your possibilities and prepare you for the staggering amount of data generated by today’s rapidly changing world.

A Powerful Certificate. Conveniently Offered.

The online Graduate Certificate in Machine Learning & Data Science Foundations is offered 100% online to help computer science professionals conveniently fit the program into their busy day-to-day lives. In addition to a flexible, convenient format, you will experience the same rigorous coursework for which Carnegie Mellon University’s graduate programs are known.

For Today’s Problem Solvers

This leading certificate program is best suited for:

Industry Professionals looking to deliver value to companies by acquiring in-demand data science, AI, and machine learning skills. After completing the program, participants will acquire the technical know-how to build machine learning models as well as the ability to analyze trends.
Recent computer science degree graduates seeking to expand their skill set and become even more marketable in a growing field. Over the past few years, data sets have grown tremendously. Today’s top companies need data science professionals who can leverage machine learning technology.

Program Name Change

To better reflect the emphasis on machine learning in the curriculum, the name of this certificate has been updated from Computational Data Science Foundations to Machine Learning & Data Science Foundations.

Although the name has changed, the course content, faculty, online experience, admissions requirements, and everything else has remained the same. Questions about the name change? Please contact us.

At a Glance

Start Date May 2024

Application Deadlines Final*: April 9, 2024

*A limited number of partial scholarships are still available. Apply by the final deadline to receive initial consideration for these awards.

Program Length 12 months

Program Format 100% online

Live-Online Schedule 1x per week for 90 minutes in the evening

Taught By School of Computer Science

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Questions? There are two ways to contact us. Call 412-501-2686 or send an email to [email protected] with your inquiries .

Looking for information about CMU's on-campus Master of Computational Data Science degree? Visit the program's website to learn more. Admissions consultations with our team will only cover the online certificate program.

A National Leader in Computer Science

Carnegie Mellon University is world renowned for its technology and computer science programs. Our courses are taught by leading researchers in the fields of Machine Learning, Language Technologies, and Human-Computer Interaction.

Number One in the nation for our artificial intelligence programs.

Number One in the nation for our programming language courses.

Number Four in the nation for the caliber of our computer science programs.

Computational thinking for the digital age: a systematic review of tools, pedagogical strategies, and assessment practices

Featured Paper
Published: 05 April 2024

Cite this article

Toluchuri Shalini Shanker Rao 1 &
Kaushal Kumar Bhagat ORCID: orcid.org/0000-0002-6861-6819 1

Computational thinking (CT) has received growing interest as a research subject in the last decade, with research contributions attempting to capitalize on the benefits that CT may provide. This study included a systematic analysis aimed at revealing current trends in the CT subject, identifying educational interventions, and emerging assessment instruments. It also gave an overview of how teachers learned CT skills and how they integrated the CT curriculum into classroom practices. We searched the data in the Web of Science database and identified 360 articles. Most importantly, it emphasized the following points: (a) the most popular subject areas in CT literature; (b) CT intervention tools; (c) CT assessment practices used so far within educational courses; and (d) effective CT approaches to influence pre-service teachers. Results from this review revealed that CT’s promotion in education had achieved significant progress in recent years. Along with the growth in the number of CT studies, the number of subjects, research questions, and teaching approaches also increased in recent years. It was also found that CT was mostly used in science, mathematics, programming, and computer science tasks, with little work in artificial intelligence (AI) and non-STEM areas. The essence of this paper implicated the researchers in designing the curriculum based on different subject domains. Furthermore, we recommended integrating augmented reality-based games using CT methodologies into the curriculum.

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Rao, T.S.S., Bhagat, K.K. Computational thinking for the digital age: a systematic review of tools, pedagogical strategies, and assessment practices. Education Tech Research Dev (2024). https://doi.org/10.1007/s11423-024-10364-y

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Stephen Ornes

Large Language Models’ Emergent Abilities Are a Mirage

Illustration of researchers taking measurements around a head sculpture.

The original version of this story appeared in Quanta Magazine .

Two years ago, in a project called the Beyond the Imitation Game benchmark , or BIG-bench, 450 researchers compiled a list of 204 tasks designed to test the capabilities of large language models , which power chatbots like ChatGPT. On most tasks, performance improved predictably and smoothly as the models scaled up—the larger the model, the better it got. But with other tasks, the jump in ability wasn’t smooth. The performance remained near zero for a while, then performance jumped. Other studies found similar leaps in ability.

The authors described this as “breakthrough” behavior; other researchers have likened it to a phase transition in physics, like when liquid water freezes into ice. In a paper published in August 2022, researchers noted that these behaviors are not only surprising but unpredictable, and that they should inform the evolving conversations around AI safety , potential, and risk. They called the abilities “ emergent ,” a word that describes collective behaviors that only appear once a system reaches a high level of complexity.

But things may not be so simple. A new paper by a trio of researchers at Stanford University posits that the sudden appearance of these abilities is just a consequence of the way researchers measure the LLM’s performance. The abilities, they argue, are neither unpredictable nor sudden. “The transition is much more predictable than people give it credit for,” said Sanmi Koyejo , a computer scientist at Stanford and the paper’s senior author. “Strong claims of emergence have as much to do with the way we choose to measure as they do with what the models are doing.”

We’re only now seeing and studying this behavior because of how large these models have become. Large language models train by analyzing enormous data sets of text —words from online sources including books, web searches, and Wikipedia—and finding links between words that often appear together. The size is measured in terms of parameters, roughly analogous to all the ways that words can be connected. The more parameters, the more connections an LLM can find. GPT-2 had 1.5 billion parameters, while GPT-3.5, the LLM that powers ChatGPT, uses 350 billion. GPT-4, which debuted in March 2023 and now underlies Microsoft Copilot , reportedly uses 1.75 trillion.

That rapid growth has brought an astonishing surge in performance and efficacy, and no one is disputing that large enough LLMs can complete tasks that smaller models can’t, including ones for which they weren’t trained. The trio at Stanford who cast emergence as a “mirage” recognize that LLMs become more effective as they scale up; in fact, the added complexity of larger models should make it possible to get better at more difficult and diverse problems. But they argue that whether this improvement looks smooth and predictable or jagged and sharp results from the choice of metric—or even a paucity of test examples—rather than the model’s inner workings.

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Three-digit addition offers an example. In the 2022 BIG-bench study, researchers reported that with fewer parameters, both GPT-3 and another LLM named LAMDA failed to accurately complete addition problems. However, when GPT-3 trained using 13 billion parameters, its ability changed as if with the flip of a switch. Suddenly, it could add—and LAMDA could, too, at 68 billion parameters. This suggests that the ability to add emerges at a certain threshold.

But the Stanford researchers point out that the LLMs were judged only on accuracy: Either they could do it perfectly, or they couldn’t. So even if an LLM predicted most of the digits correctly, it failed. That didn’t seem right. If you’re calculating 100 plus 278, then 376 seems like a much more accurate answer than, say, −9.34.

So instead, Koyejo and his collaborators tested the same task using a metric that awards partial credit. “We can ask: How well does it predict the first digit? Then the second? Then the third?” he said.

Koyejo credits the idea for the new work to his graduate student Rylan Schaeffer, who he said noticed that an LLM’s performance seems to change with how its ability is measured. Together with Brando Miranda, another Stanford graduate student, they chose new metrics showing that as parameters increased, the LLMs predicted an increasingly correct sequence of digits in addition problems. This suggests that the ability to add isn’t emergent—meaning that it undergoes a sudden, unpredictable jump—but gradual and predictable. They find that with a different measuring stick, emergence vanishes.

Brando Miranda (left), Sanmi Koyejo, and Rylan Schaeffer (not pictured) have suggested that the “emergent” abilities of large language models are both predictable and gradual.

But other scientists point out that the work doesn’t fully dispel the notion of emergence. For example, the trio’s paper doesn’t explain how to predict when metrics, or which ones, will show abrupt improvement in an LLM, said Tianshi Li , a computer scientist at Northeastern University. “So in that sense, these abilities are still unpredictable,” she said. Others, such as Jason Wei, a computer scientist now at OpenAI who has compiled a list of emergent abilities and was an author on the BIG-bench paper, have argued that the earlier reports of emergence were sound because for abilities like arithmetic, the right answer really is all that matters.

“There’s definitely an interesting conversation to be had here,” said Alex Tamkin , a research scientist at the AI startup Anthropic. The new paper deftly breaks down multistep tasks to recognize the contributions of individual components, he said. “But this is not the full story. We can’t say that all of these jumps are a mirage. I still think the literature shows that even when you have one-step predictions or use continuous metrics, you still have discontinuities, and as you increase the size of your model, you can still see it getting better in a jump-like fashion.”

And even if emergence in today’s LLMs can be explained away by different measuring tools, it’s likely that won’t be the case for tomorrow’s larger, more complicated LLMs. “When we grow LLMs to the next level, inevitably they will borrow knowledge from other tasks and other models,” said Xia “Ben” Hu , a computer scientist at Rice University.

This evolving consideration of emergence isn’t just an abstract question for researchers to consider. For Tamkin, it speaks directly to ongoing efforts to predict how LLMs will behave. “These technologies are so broad and so applicable,” he said. “I would hope that the community uses this as a jumping-off point as a continued emphasis on how important it is to build a science of prediction for these things. How do we not get surprised by the next generation of models?”

Original story reprinted with permission from Quanta Magazine , an editorially independent publication of the Simons Foundation whose mission is to enhance public understanding of science by covering research developments and trends in mathematics and the physical and life sciences.

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Nine Science Terps Awarded 2024 National Science Foundation Graduate Research Fellowships

Nine current students and recent alums of the University of Maryland’s College of Computer, Mathematical, and Natural Sciences (CMNS) received prestigious National Science Foundation (NSF) Graduate Research Fellowships , which recognize outstanding graduate students in science, technology, engineering, and mathematics.

Across the university, 22 current students and recent alums were among the 2024 fellowship winners announced by the NSF. The college’s nine awardees include four current graduate students and five recent alums.

CMNS graduate student recipients:

Mikayla Greiner, biophysics
Megan Ma, entomology
Sadia Nourin (B.S. ’23, computer science; B.S. ’23, finance), computer science
Emily Wisinski, atmospheric and oceanic science

CMNS alum recipients:

Marcus Benyamin (B.S. ’17, mathematics ; B.S. ’17, chemical engineering)
Kaitlyn Dold (B.S. ’22, chemistry )
Katharina Krstic (B.S. ’22, chemistry )
Siri Neerchal (B.S. ’21, mathematics ; B.S. ’21, history)
Ashley Weiss (B.S. ’22, biological sciences )

NSF fellows receive three years of support, including a $37,000 annual stipend, a $16,000 cost-of-education allowance for tuition and fees, and access to opportunities for professional development.

The NSF Graduate Research Fellowship Program helps ensure the vitality of the human resource base of science and engineering in the United States and reinforces its diversity. The program recognizes and supports outstanding graduate students in NSF-supported science, technology, engineering, and mathematics disciplines who are pursuing research-based master’s and doctoral degrees at accredited U.S. institutions.

Since 1952, NSF has funded more than 60,000 Graduate Research Fellowships out of more than 500,000 applicants. At least 42 fellows have gone on to become Nobel laureates and more than 450 have become members of the National Academy of Sciences.

About the College of Computer, Mathematical, and Natural Sciences

The College of Computer, Mathematical, and Natural Sciences at the University of Maryland educates more than 8,000 future scientific leaders in its undergraduate and graduate programs each year. The college's 10 departments and six interdisciplinary research centers foster scientific discovery with annual sponsored research funding exceeding $250 million.

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Computer and information research scientists design innovative uses for new and existing technology. They study and solve complex problems in computing for business, science, medicine, and other ... Analytical skills. Computer and information research scientists must be organized in their thinking and analyze the results of their research to ...
How to Become a Computer and Information Research Scientist?
Computer and Information Research Scientist Skills. An aspiring computer and information research scientist should have a strong knowledge of the core aspects of computer systems like programming languages, coding, software development, technical writing, etc. Apart from these, as a computer scientist, here are some skills you should ensure you have in your arsenal.
Computer and Information Research Scientists
The median annual wage for computer and information research scientists is $131,490. The median wage is the wage at which half the workers in an occupation earned more than that amount and half earned less. The lowest 10 percent earned less than $74,210, and the highest 10 percent earned more than $208,000.
How to Become a Computer and Information Research Scientist
These programs teach important skills in programming, statistics, machine learning, and predictive modeling. To become a computer and information research scientist, aspiring professionals also need to complete a postgraduate degree, such as Maryville University's online Master's in Data Science. In this program, students build on their ...
What's a Computer Scientist? And How to Become One
Computer and information research scientist: $136,620 . Computer network architect: $126,900 . ... With constant advancements being made in tech, it's critical for you to constantly develop your computer science skills to keep up with the latest technologies and techniques. A blend of technical skills and workplace skills is necessary to find ...
Top Skills for Research Scientists in 2024 (+Most Underrated Skills)
Technical proficiency in emerging technologies is a key skill for Research Scientists as we enter 2024. With rapid advancements in fields such as genomics, nanotechnology, and computational biology, staying abreast of the latest tools and techniques is crucial.
Computer Research Scientist Career Path
Computer and information research scientists analyze data to develop innovative new technologies and solutions. Keep reading to find out more. ... There are several skills that an individual should have if they wish to be a computer and information research scientist. Computer engineers and scientists must possess analytical minds and be able ...
How to Become a Computer and Information Research Scientist
1. Get a Degree in Computer Science or a Related Field. Computer and information science is a field that requires a deep understanding of the theories of computing and data processing. Therefore, getting a computer science/engineering degree or any related field is the first step. It would be best to go for something higher than a college ...
How to Become a Computer Scientist
Ph.D. Degree: A Doctor of Philosophy (Ph.D.) in computer science is a research-focused degree that can take anywhere from four to six years or more to complete. The duration depends on the student's research progress, the complexity of the research topic, and other factors specific to the individual's work.
What Does a Computational Scientist Do? 2024 Career Guide
Computational scientist skills. Computational scientists need a strong background in mathematics, analysis, and computer technology to succeed. ... (BLS), computer and information research scientist roles, which are similar to computational scientists, may grow about 23 percent from 2022 to 2032, a rate significantly faster than the average for ...
Skills Computer Scientists Should Have
Skills Computer Scientists Should Have. Computer scientists use research and innovative thinking to improve current technology and solve problems. The Bureau of Labor Statistics (BLS) projects jobs for computer and information research scientists to grow 22% from 2020-2030, which is much faster than average. The organization reports a median ...
What does a Research Scientist do? Role & Responsibilities
Research scientists conduct laboratory-based experiments and trials and work in many fields including medicine, political science, computer science, and environmental science. They plan and conduct experiments that become topics of research papers and reports. They collect samples and carry out other types of field research and monitor their ...
CMU's Online Graduate Certificate in Machine Learning and Data Science
Computer-Science Based Data Analytics. When you enroll in this program, you will learn foundational skills in computer programming, machine learning, and data science that will allow you to leverage data science in various industries including business, education, environment, defense, policy and health care.
Computational thinking for the digital age: a systematic review of
In this study the Web of Science (WoS) database was searched to find the relevant data. This database was chosen because it indexes high-quality social science research articles (Ezeamuzie & Leung, 2022).Also, WoS is often recommended by researchers for its provision of bibliographic data for individual articles and information about their cited references (Liu & Xia, 2021; Lee et al., 2022).
Large Language Models' Emergent Abilities Are a Mirage
Others, such as Jason Wei, a computer scientist now at OpenAI who has compiled a list of emergent abilities and was an author on the BIG-bench paper, have argued that the earlier reports of ...
10 GitHub Repositories to Master Computer Science
However, the open-source community on GitHub has created a wealth of resources that can guide you through this journey. In this blog post, we will explore 10 essential GitHub repositories that can help you learn the necessary concepts and tools to master computer science and secure a job at a top tech company. 1. Developer Roadmap.
Nine Science Terps Awarded 2024 National Science Foundation Graduate
Nine current students and recent alums of the University of Maryland's College of Computer, Mathematical, and Natural Sciences (CMNS) received prestigious National Science Foundation (NSF) Graduate Research Fellowships, which recognize outstanding graduate students in science, technology, engineering, and mathematics. Across the university, 22 current students and recent alums were among the ...
19th Annual CS Research Symposium
Posted on 2023-04-05. The 19th Annual CS Research Symposium was held on Friday, March 29. During the event, students shared their ongoing research in two presentation sessions and a poster session. A panel of faculty judges evaluated the submissions.
Universal brain-computer interface lets people play games with just
Chicago. University of Texas at Austin. "Universal brain-computer interface lets people play games with just their thoughts." ScienceDaily. ScienceDaily, 1 April 2024. <www.sciencedaily.com ...
Professor Cheng Gong at ECE Spring 2024 Colloquium
Brief Bio of Prof. GongProfessor Cheng Gong is an assistant professor in the Department of Electrical and Computer Engineering at the University of Maryland, College Park. His research group focuses on 2D quantum materials and devices. He is a recipient of IUPAP Young Scientist Prize in Semiconductor Physics 2020.