Developing educational materials for college-level courses in Computer Science, Data Science, and Cybersecurity.
Assisting in the preparation of at least two conference submissions (e.g., ACM SIGCSE, SIGITE, ITiCSE, or IEEE FIE).
Designing and implementing full-cycle educational labs that apply AI/ML/Data Science techniques to cybersecurity problems, including problem formulation, data generation, preprocessing, feature engineering, model development, and pipeline testing.
Creating containerized environments (e.g., Docker) and virtual machine images to support reproducible lab deployment.
Contributing to the design of a Capture-the-Flag (CTF)-style gaming environment for teaching and testing attack/defense strategies.
Maintaining clear documentation, collaborating with the research team, and contributing to project dissemination through reports and presentations.

Required Qualifications*

UM-Flint undergraduate student
Strong programming skills (e.g., Python, C/C++, or Java) and ability to quickly learn new tools and frameworks.
Reliability, strong organizational skills, and the ability to work independently while meeting deadlines.
Good written and verbal communication skills for documenting results and contributing to publications.
Interest in computer science, data science, machine learning, or cybersecurity.
Willingness to learn and apply new technical skills as needed.

Desired Qualifications*

Familiarity with containerization (e.g., Docker) and virtual machine environments.
Experience with data preprocessing, feature engineering, or machine learning workflows.
Prior exposure to cybersecurity concepts or hands-on lab environments.
Having taken Data structures, algorithms, Theory of computation courses with a good grade

Modes of Work

Hybrid
The work requirements allow both onsite and offsite work and an employee has an expected recurring onsite presence. On occasion, the employee may be required and must be available to work onsite more frequently if necessitated by unit leadership or their designee and/or the job requirements.

Positions that are eligible for hybrid or mobile/remote work mode are at the discretion of the hiring department. Work agreements are reviewed annually at a minimum and are subject to change at any time, and for any reason, throughout the course of employment. Learn more about the work modes.

Background Screening

The University of Michigan conducts background checks on all job candidates upon acceptance of a contingent offer and may use a third party administrator to conduct background checks. Background checks are performed in compliance with the Fair Credit Reporting Act.

Application Deadline

Job openings are posted for a minimum of three calendar days. The review and selection process may begin as early as the fourth day after posting. This opening may be removed from posting boards and filled anytime after the minimum posting period has ended.