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Scientific Computing Internship Jobs in Illinois

TransUnion

Data Science Platform Developer

Chicago, IL · On-site

... scientific computing. * Provide oversight and hands-on support for the development of analytic ... interns on a project basis, as needed. * Participate in interviewing and evaluation of new talent ...

Cccis

Data Science Engineer Internship

Chicago, IL · On-site

$20 - $43/hr

Interns work on real pipelines and real datasets serving the auto-insurance industry and internal ... Unix commands and scripting; distributed computing and lakehouse fundamentals; Generative AI, and ...

RBN

Lead Software Engineer

Chicago, IL

Hire, mentor and manage software engineers and interns from the Computer Science department ... computing and electronic trading Facilitate and participate in sharing best practices with other ...

RBN Chicago

Lead Software Engineer

Chicago, IL · On-site

Hire, mentor and manage software engineers and interns from the Computer Science department ... computing and electronic trading Facilitate and participate in sharing best practices with other ...

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Scientific Computing Internship information

What is a scientific computing internship?

A Scientific Computing Internship is a temporary position where students or recent graduates work on projects involving computational methods to solve scientific problems. Interns typically assist with programming, data analysis, mathematical modeling, and using specialized software to support research in fields like physics, biology, or engineering. The internship provides hands-on experience with real-world scientific challenges, often in academic, government, or industry research settings. These opportunities help interns develop technical skills, gain exposure to the research process, and build professional networks in the scientific computing field.

What types of projects might I work on during a scientific computing internship?

As a Scientific Computing Intern, you may be involved in projects such as developing simulation models, optimizing computational algorithms, or analyzing large datasets for scientific research. Interns often collaborate closely with researchers and software engineers, contributing to code development, data processing, or scientific visualization tasks. These projects provide hands-on experience with programming languages like Python, MATLAB, or C++, and exposure to high-performance computing environments. The collaborative and interdisciplinary nature of the work allows you to build both technical and teamwork skills which are valuable for future roles in academia or industry.

What are the key skills and qualifications needed to thrive as a scientific computing intern, and why are they important?

To thrive as a Scientific Computing Intern, you generally need a solid background in mathematics, programming (often Python, C++, or MATLAB), and data analysis, typically supported by coursework in computer science or a related STEM field. Familiarity with scientific computing tools and libraries such as NumPy, SciPy, and version control systems like Git is common, and experience with high-performance computing environments is a plus. Strong problem-solving abilities, attention to detail, and effective communication skills help interns collaborate with research teams and present complex findings clearly. These qualifications are crucial for efficiently supporting research projects and contributing to innovative scientific solutions.

What is the difference between Scientific Computing Internship vs Data Analyst Internship?

AspectScientific Computing InternshipData Analyst Internship
Required CredentialsTypically requires a background in computer science, mathematics, or engineering; familiarity with programming languages like Python, C++, or MATLABUsually requires a degree in statistics, mathematics, or related fields; skills in SQL, Excel, and data visualization tools
Work EnvironmentResearch labs, academic institutions, or R&D departments within tech or engineering firmsBusiness settings, finance, marketing, or healthcare organizations
Employer & Industry UsageUsed in scientific research, simulations, and modeling projectsApplied in business analytics, reporting, and data-driven decision making

While both internships involve working with data and computational tools, Scientific Computing Internships focus on scientific research, simulations, and technical problem-solving, whereas Data Analyst Internships emphasize analyzing business data to inform decisions. The choice depends on your career interests in research versus business analytics.

What are the most commonly searched types of Scientific Computing jobs in Illinois?

The most popular types of Scientific Computing jobs in Illinois are:

What are popular job titles related to Scientific Computing Internship jobs in Illinois?

For Scientific Computing Internship jobs in Illinois, the most frequently searched job titles are:

What job categories do people searching Scientific Computing Internship jobs in Illinois look for?

The top searched job categories for Scientific Computing Internship jobs in Illinois are:

Scientific Computing Internship jobs near you

Postbaccalaureate Appointee - Machine Learning for Viral Glycosylation Prediction

Argonne National Laboratory

Lemont, IL • On-site

Full-time

Posted 10 days ago

Job description

The Computing, Environment, and Life Sciences (CELS) directorate at Argonne National Laboratory is seeking a Post-Bachelor Appointee to contribute to research at the intersection of artificial intelligence, computational biology, and high-performance computing.
  • The successful candidate will join an interdisciplinary team developing machine learning approaches to understand glycosylation patterns across viral proteins, supporting research that advances computational methods for pathogen characterization, vaccine design, and therapeutic discovery.
  • Working under the guidance of experienced computational scientists, the appointee will assist in the development, implementation, validation, and evaluation of machine learning models for predicting glycosylation sites and glycan occupancy in viral proteins.
  • The position offers an opportunity to develop technical expertise in machine learning, computational biology, scalable software development, and scientific computing while gaining experience in a collaborative national laboratory research environment.

In this role, you can expect to:
  • Assist in the development, implementation, and evaluation of machine learning models for predicting glycosylation sites and glycosylation patterns in viral proteins.
  • Support the design and implementation of graph neural network (GNN) models and other deep learning approaches for learning sequence- and structure-based representations of viral proteins.
  • Collect, curate, preprocess, and integrate biological sequence, structural, and experimental datasets used for model development and benchmarking.
  • Develop software tools and computational workflows using modern machine learning frameworks such as PyTorch, PyTorch Geometric, TensorFlow, or related libraries.
  • Conduct model training, validation, benchmarking, and performance analysis using appropriate statistical and computational evaluation methods.
  • Assist in deploying and optimizing machine learning workflows on Argonne's high-performance computing systems.
  • Document software, datasets, computational workflows, and experimental results to promote reproducibility and maintainability.
  • Collaborate with computational scientists, biologists, and software engineers to interpret model predictions and improve computational methods.
  • Prepare technical reports, presentations, and documentation summarizing research progress and computational results.
  • Contribute to manuscripts, conference presentations, software releases, and other research dissemination activities as appropriate.
  • Participate in project meetings, technical discussions, and collaborative research activities across multidisciplinary teams.
  • Perform additional research and technical duties assigned by the supervisor in support of project objectives.

Expected Outcomes:
  • Success in this position will be demonstrated through:
  • Development of reproducible computational workflows supporting machine learning research on viral glycosylation.
  • Successful implementation and evaluation of machine learning models under the guidance of project scientists.
  • Contribution to scalable software and computational tools supporting ongoing research activities.
  • Effective collaboration within multidisciplinary teams.
  • Preparation of high-quality technical documentation, reports, and research presentations.
  • Growth in technical and research capabilities that prepare the appointee for graduate study or advanced research positions.

Position Requirements
Required Qualifications:
  • Recently completed Bachelor's degree in Computer Science, Bioinformatics, Computational Biology, Data Science, Biomedical Engineering, Applied Mathematics, or a related STEM discipline.
  • Experience programming in Python or a similar scientific programming language.
  • Basic knowledge of machine learning or deep learning methods.
  • Familiarity with one or more machine learning frameworks such as PyTorch, TensorFlow, or JAX.
  • Experience analyzing scientific or biological datasets through coursework, research projects, or internships.
  • Strong analytical and problem-solving skills.
  • Excellent written and verbal communication skills.
  • Demonstrated ability to work effectively both independently and as part of an interdisciplinary research team.
  • Ability to model Argonne's core values of impact, safety, respect, teamwork, ang integrity.

Preferred Qualifications:
  • Undergraduate research experience in machine learning, computational biology, bioinformatics, or related fields.
  • Experience with graph neural networks or representation learning.
  • Familiarity with protein sequence analysis, structural biology, glycobiology, or bioinformatics.
  • Experience using Linux environments, Git, and software development best practices.
  • Exposure to GPU computing, high-performance computing, or cloud computing environments.
  • Experience presenting research findings or contributing to scientific publications or open-source software projects.

Job Family
Temporary
Job Profile
Postbaccalaureate Appointee
Worker Type
Long-Term (Fixed Term)
Time Type
Full time
The expected hiring range for this position is $58,656.00-$92,273.00.
Please note that the pay range information is a general guideline only. The pay offered to a selected candidate will be determined based on factors such as, but not limited to, the scope and responsibilities of the position, the qualifications of the selected candidate, business considerations, internal equity, and external market pay for comparable jobs. Additionally, comprehensive benefits are part of the total rewards package.
Click here to view Argonne employee benefits!
As an equal employment opportunity employer, and in accordance with our core values of impact, safety, respect, integrity and teamwork, Argonne National Laboratory is committed to a safe and welcoming workplace that fosters collaborative scientific discovery and innovation. Argonne encourages everyone to apply for employment. Argonne is committed to nondiscrimination and considers all qualified applicants for employment without regard to any characteristic protected by law.
Argonne employees, and certain guest researchers and contractors, are subject to particular restrictions related to participation in Foreign Government Sponsored or Affiliated Activities, as defined and detailed in United States Department of Energy Order 486.1A. You will be asked to disclose any such participation in the application phase for review by Argonne's Legal Department.
All Argonne offers of employment are contingent upon a background check that includes an assessment of criminal conviction history conducted on an individualized and case-by-case basis. Please be advised that Argonne positions require upon hire (or may require in the future) for the individual be to obtain a government access authorization that involves additional background check requirements. Failure to obtain or maintain such government access authorization could result in the withdrawal of a job offer or future termination of employment.

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