State Legislative Science, Technology, and Public Policy Fellow

Overview

The Science, Technology and Public Policy (STPP) program at the Gerald R. Ford School of Public Policy has launched MiST, a Michigan Science, Technology, and Public Policy Fellowship program. MiST embeds fellows in state government offices in Lansing, Michigan for twelve months. The fellow is focused on AI policy and governance related to the priorities and work of the Department of Environment, Great Lakes, and Energy (EGLE).

The fellow will work a hybrid schedule with 1-2 days in-person per week at EGLE's offices for the full appointment.

• Research 35%
  • Conduct literature and landscape reviews on AI governance and related policy topics (e.g., innovation policy, data centers, data governance, data privacy, responsible AI use and implementation).
  • Track key bills, hearings, and developments at the federal level and in other states on AI and data governance.
  • Engage in online research using state government and university library databases and conduct in-person information gathering as needed.
  • Collaborate with EGLE team members on shared research and policy projects.
• Communications and Findings Dissemination 20%
  • Draft memos, presentations, briefs, and reports intended for non-technical audiences.
  • 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 and communicate them accordingly.
  • Maintain 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.

• 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 effective writing, presentation, or public speaking skills.
• Some experience with data analysis within AI implementation tools.
• Advanced knowledge and/or experience in one or more areas of Artificial Intelligence, including AI implementation, AI policy, AI development, responsible AI, usage and adoption trends, or AI governance.
• Ability to prioritize efforts across multiple simultaneous projects and manage time efficiently.
• Familiarity with multiple AI models, such as frontier or specialized models.

One-year term-limited appointment with renewal for a second year dependent on continued grant funding. The position requires working both in-person in Lansing at EGLE and remotely. The fellow will receive training on Michigan state government, policy processes, policy writing, science communication to non-scientific audiences, and evidence-based, objective communications to clarify technical topics. EGLE staff will manage day-to-day work, and the fellow will report to the EGLE Information Management Division Director.

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