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How much do theoretical computer science internship jobs pay per hour?

As of May 31, 2026, the average hourly pay for theoretical computer science internship in the United States is $17.31, according to ZipRecruiter salary data. Most workers in this role earn between $14.42 and $19.23 per hour, depending on experience, location, and employer.

What are the key skills and qualifications needed to thrive as a Theoretical Computer Science Intern, and why are they important?

To thrive as a Theoretical Computer Science Intern, you need a strong background in mathematics, algorithms, and discrete structures, often supported by coursework in computer science or mathematics. Familiarity with programming languages (such as Python or C++), LaTeX for documentation, and version control systems like Git is typically expected. Analytical thinking, problem-solving, and effective written communication are standout soft skills for this role. These skills are crucial for tackling complex theoretical problems, collaborating on research, and clearly presenting findings in both academic and professional environments.

What types of projects do interns typically work on during a Theoretical Computer Science Internship?

During a Theoretical Computer Science Internship, interns often work on projects involving algorithm design, computational complexity, graph theory, or cryptography. These projects may include analyzing and improving existing algorithms, developing proofs of concept, or researching open problems under the guidance of senior researchers. Interns usually collaborate closely with other interns and full-time researchers, participate in regular group meetings, and are encouraged to present their findings. The work is generally research-oriented and may involve reading academic papers, writing reports, and sometimes contributing to publications.

What is a Theoretical Computer Science Internship?

A Theoretical Computer Science Internship is a temporary position, typically for students or recent graduates, focused on research and problem-solving within the foundational areas of computer science. Interns in this role explore topics such as algorithms, computational complexity, cryptography, and formal methods. They often work on mathematical proofs, theoretical models, or simulations under the guidance of experienced researchers or faculty. The internship provides valuable experience in academic research, logical reasoning, and advanced problem-solving, preparing participants for further study or research-oriented careers.

What is the difference between Theoretical Computer Science Internship vs Data Science Internship?

AspectTheoretical Computer Science InternshipData Science Internship
Required CredentialsTypically requires computer science or related degrees, strong math backgroundRequires statistics, programming, and data analysis skills
Work EnvironmentResearch labs, academic settings, tech companies focusing on algorithms and theoryBusiness, tech companies, analytics firms working on data modeling and insights
Industry UsageAcademic research, R&D departments, tech industryBusiness analytics, marketing, finance, tech industry

Theoretical Computer Science Internships focus on algorithm development, computational theory, and mathematical foundations, often in research or academic settings. Data Science Internships emphasize data analysis, machine learning, and practical application of statistical methods in business or tech environments. While both require strong programming skills, their core focus and industry applications differ significantly.

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Theoretical Computer Science Internship jobs near you

Cryptologic Computer Scientist

GRVTY

Fort George G Meade, MD

Other

Posted 28 days ago

Job description

What Impact You'll Have

  • GRVTY is seeking experienced Cryptologic Computer Scientist to design, develop, deliver, and operate solutions to hard cryptologic computer science problems within a scientific framework.You will create solutions derived from forensics and attack attribution, facilitate protection of critical networks and active systems, and conduct knowledge discovery of passive and active systems, or other cryptologic computer science mission support.

What You'll be Owning

  • The right candidate will apply requisite computer science skills (operating systems, compiler theory, databased theory, algorithm analysis, computer architecture, discrete math, programming language theory, and data structure) to each problem to provide state-of -the-art techniques, tools, and approaches.  This particular position will be a hybrid computer scientist/cyber threat analyst, specifically using Python, Spark/PySpark, and you will need to have a strong network and protocol analysis background and familiarity with customer tools. 

What You Must Have

  • Master's degree with 6 years of relevant experience.
  • Bachelor's Degree with 8 years of relevant experience.
  • Associates degree with 10 years of relevant experience.  
  • Degree must be in Computer Science, Computer Engineering, Electrical Engineering, Mathematics, or a related field with at least one programming and at least 4 upper-level math classes (Calculus and above).  
  • Relevant experience must be in a computer science area (i.e. theoretical or applied), simulation/model development, designing/developing/using/evaluating mathematic models, methods, and/or techniques (e.g. algorithm or development) computation science, algorithm analysis and design, reverse engineering, and/or designing/developing computer and information systems, including engineering hardware and/or software.   
  • Strong Python, Spark/PySpark skills.
  • Strong Network and Protocol Analysis background.
  • Familiarity with customer tools.
  • TS SCI w/ poly

What Would be Nice to Have

  • Design, develop, deliver, and operate solutions to hard cryptologic computer science problems within a scientific framework.  
  • The solutions may arise in the forms of forensics and attack attribution, protection of critical networks, active systems warnings and indicators, active penetration into target systems, knowledge discovery of passive and active systems, or other cryptologic computer science mission support.  
  • Requisite computer science skills (operating systems, compiler theory, database theory, algorithm analysis, computer architecture, discrete math, programming language theory, and data structures are applied to each problem to provide state of the art techniques, tools, and approaches).

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