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Scientific Computing Internship Jobs in Wisconsin

... computing (GPU/CPU) on Linux, with a focus on C++ and OpenCL. This internship is designed for ... Minimum Qualifications Current junior standing (or equivalent progress) in Computer Science ...

Jr. Cloud Engineer

Madison, WI · Hybrid

$56.25 - $75/hr

Basic understanding of cloud computing concepts and services. * Foundational knowledge of ... Experience through internships, labs, personal projects, coursework, or certifications.

Jr. Cloud Engineer

Madison, WI · On-site

$56.25 - $75/hr

Basic understanding of cloud computing concepts and services. * Foundational knowledge of ... Experience through internships, labs, personal projects, coursework, or certifications.

Scientific Computing Internship information

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 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 are the most commonly searched types of Scientific Computing jobs in Wisconsin? The most popular types of Scientific Computing jobs in Wisconsin are:
What cities in Wisconsin are hiring for Scientific Computing Internship jobs? Cities in Wisconsin with the most Scientific Computing Internship job openings:
Infographic showing various Scientific Computing Internship job openings in Wisconsin as of August 2026, with employment types broken down into 8% Internship, 1% As Needed, 65% Full Time, 24% Part Time, 1% Temporary, and 1% Contract. Highlights an 86% Physical, 1% Hybrid, and 13% Remote job distribution.

$206K/yr

Full-time

Posted 28 days ago


Job description

Description

The Research Software Engineer (RSE) will work to bring modern software engineering techniques and approaches to research projects at the institute as part of long-running engagements and collaborations between scientists. At Morgridge, the RSE will sit at the nexus of exciting research, large-scale computing, and national cyberinfrastructure projects. Whether it's using agentic AI to enhance a codebase, making data transfers more robust, or making workloads run more effectively across thousands of cores, the RSE will have a diversity of challenges and help advance Morgridge's goals of Fearless Science. The initial projects will focus on development of the Pelican Platform, which is used for a distributed data delivery and transfer system across the US.

The position will work in the Morgridge Research Computing theme and with the Center for High Throughput Computing (CHTC) at the UW-Madison; these groups are led by PIs who lead cyberinfrastructure projects such as the Partnership to Advance Throughput Computing (PATh), a major NSF investment in the vision that high throughput computing can make an outsized impact on science, and the Pelican Platform. Combined, the teams have about 25 staff members, operate 25,000 computing cores and over 300 GPUs, and interacts with over 100 external universities - ensuring there are always interesting challenges in distributed systems.


The team heavily leverages agentic AI as part of the development workflows: understanding of system fundamentals (thinking through components may interact, potential failure points, designing testing regimes) and reviewing code changes are more important than writing code in a specific language.


Primary Responsibilities

  • Interact with scientific group leaders and the Research Computing leads to identify pressing software engineering challenges and scoping / architecting / implementing / supporting a program of work to solve them.
  • Develop distributed systems code bases (typically languages include Go but C++ and Python are also used) to make them more robust or implement new functionality.
  • Assist the operations team in debugging distributed systems and to deploy newly-developed features.
  • As aligned with experience, lead student software engineering interns on specific semester-long projects.
  • Provide assistance with other projects, as necessary to support the overall mission and goals of the Morgridge Institute for Research

Requirements

To perform this job successfully, an individual must be able to perform each primary duty satisfactorily. Some of the duties can be learned through on-the-job training. The requirements listed below are representative of the knowledge, skill, and/or ability required. Reasonable accommodation may be made to enable individuals with disabilities to perform the primary duties.


Education and Experience:

  • A Bachelor's degree in Computer Science, Mathematics, Physics, or biological sciences; Master's degree preferred.
  • 1+ years of working with software engineering, preferably in a research environment; 3+ years preferred.
  • Programming experience in either Go, Python or C++; Go preferred.
  • Experience in utilizing large-scale computing environments such as batch or cloud is preferred.

Knowledge, Skills and Abilities Required:

  • Strong systems design and programming skills.
  • Experience in writing design documents as part of feature design
  • Ability to keep projects organized in a project management / issuer tracker system such as JIRA.
  • Familiarity of software development environments like GitHub and modern CI/CD tooling such as GitHub Actions or Jenkins.
  • Knowledge of working with the following technologies and environments is desired: HTCondor, Containers/Kubernetes, Pelican, or federally-funded cyberinfrastructure.

Working Conditions and Physical Effort:

  • Work is normally performed in a typical office environment.
  • Day-to-day, no or very limited physical effort is required.
  • No or very limited exposure to physical risk.