Job Title
State Legislative Science, Technology, and Public Policy Fellow
Job ID
280243
Location
Ann Arbor Campus
City
Ann Arbor
State
MI
Regular/Temporary
Regular
Full/Part Time
Full-Time
Mode of Work
Hybrid
Job Title
Research Area Specialist Inter
Appointing Department
G. Ford Sc Pub Pol
Posting Begin Date
07/16/2026
Posting End Date
08/09/2026
Salary From
62000.00
Salary To
70000.00
Date Closed
 
FLSA Status
Exempt

How to Apply

 
  • Applicants must submit a resume, cover letter, and writing sample to be considered. Please combine all materials into a single document. The cover letter should explain your interest in the position and highlight relevant skills and experience. The writing sample should be no more than 10 pages and should demonstrate strong professional writing skills. Policy-related samples, such as a policy memo, briefing paper, analysis, report, or similar document, are preferred.
  • This is one-year term-limited appointment and renewal for a second year is dependent on continued grant funding.
  • This position requires working both in-person in Lansing at the Department of Environment, Great Lakes, and Energy and remotely.

IMPORTANT NOTE: ***Please do not use AI tools in any part of the application process (drafting your cover letter, answering questions during the interview, etc).***  We are interested in assessing your qualifications without the input of AI assistance.

Job Summary

 

The Science, Technology and Public Policy (STPP) program at the Gerald R. Ford School of Public Policy has recently launched MiST, the Michigan Science, Technology, and Public Policy Fellowship program, which embeds fellows in offices in state government in Lansing, Michigan for twelve months. MiST is currently recruiting for a one-year post-graduate state legislative fellowship position focused on AI policy and governance as it relates to the priorities and work of the Department of Environment, Great Lakes, and Energy. The fellow is expected to work hybrid schedule with 1-2 days in-person per week at EGLE's offices for the full appointment.

To ensure a successful fellowship year, the fellow will receive training about Michigan state government, the policy process, policy writing instruction, communicating science and technology to non-scientific audiences, and  how to provide evidence-based, objective communications that help expand or clarify technical topics. Staff at EGLE will manage the day-to-day work of the fellow and you will report to Brad Pagratis, EGLE Information Management Division Director.

The MiST fellowship program is administered by the Ford School, one of the nation's foremost policy schools at one of the world's great public universities. We are a community dedicated to the public good. We inspire and prepare leaders grounded in service, conduct transformational research, and collaborate on evidence-based policymaking to take on our communities' and our world's most pressing challenges. To learn more about the Ford School, read About Us.

Responsibilities*

 
  • Research 35%
    • Conduct literature and landscape reviews on AI governance and other technology related policy topics (e.g., innovation policy, data centers, data governance, data privacy, and responsible AI use and implementation).
    • Track key bills, hearings, new developments at Congress, federal agencies and other states on AI and/or data governance 
    • Engage in online research using state government and university library  databases and conduct in-person information gathering as needed.
    • Work with team members at EGLE to collaborate on shared research and policy projects 
  • Communications and Findings Dissemination 20%
    • Draft memos, presentations, briefs, and reports intended for a non-technical audience
    • Assist in creating and maintaining print and web-based resources
    • Present findings to supervisors and staff
  • Agency and government relations 10%
    • Respond to queries on technology policy
    • Determine research needs and priorities for the questions posed and communicate them accordingly 
    • Practice confidentiality in work communications.
  • Data Analysis and AI system analysis 35%
    • Research and develop strategies for large scale data clean-up, data quality, and data governance initiatives
    • Perform data cleaning and merging procedures on complex data sets
    • Review system documentation from AI implementations
    • Review, analyze, and make recommendations on model training data 
    • Assist with data analysis, including preparing data analysis results for memos and presentations
    • Review and compare system model cards and model information

Required Qualifications*

 
  • Fellows must hold a terminal degree (Ph.D. or equivalent) in natural sciences (e.g., biology, physics, earth), social sciences (e.g., economics, education, sociology), engineering, technology, or a related discipline. Degrees must be conferred by the fall / summer of 2026
  • Experience synthesizing scientific research and/or technical topics for non-specialist audiences through the use of effective writing, presentation, or public speaking skills
  • Some experience with data analysis within AI implementation tools
  • Advanced knowledge and / or experience of one or more areas of Artificial Intelligence, including but not limited to AI implementation, AI policy, AI development, responsible AI, usage and adoption trends, or AI governance.
  • Ability to prioritize efforts across multiple simultaneous projects and to manage time efficiently
  • Familiarity or use with multiple AI models, such as frontier or specialized

Why Work at Michigan?

 

In addition to a career filled with purpose and opportunity, The University of Michigan offers a comprehensive benefits package to help you stay well, protect yourself and your family and plan for a secure future. Benefits include:

  • Generous time off
  • A retirement plan that provides two-for-one matching contributions with immediate vesting
  • Many choices for comprehensive health insurance
  • Life insurance
  • Long-term disability coverage
  • Flexible spending accounts for healthcare and dependent care expenses
  • Paid parental leave

Modes of Work

 

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.

Application Deadline

 

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

U-M EEO Statement

 

The University of Michigan is an Equal Opportunity Employer. We are committed to providing an environment of mutual respect where equal employment opportunities are available to all applicants, including protected veterans and individuals with disabilities.