Interested candidates should submit a single PDF containing the following to Prof. Sherif El-Tawil at [email protected]
- A Cover Letter explicitly detailing your experience in agentic AI/LLMs and confirming your availability for a two-year minimum commitment.
- A detailed Curriculum Vitae (CV) including links to public code repositories or portfolio projects (e.g., GitHub), if applicable.
- A Research Statement (1-2 pages) highlighting your AI background and vision for human-agentic teaming in complex physical systems.
- Contact information for three professional references.
The Department of Civil and Environmental Engineering at the University of Michigan invites applications for a Postdoctoral Research Fellow to lead the AI architecture development for the newly launched initiative: MResilience-HAACUR (Center for Human-Agentic AI Collaboration for Urban Resilience). Working under the supervision of Prof. Sherif El-Tawil (Civil Engineering) and Atul Prakash (Computer Science), the successful candidate will serve as a key architect for an AI-enabled urban operations simulation platform.
This interdisciplinary initiative connects agentic AI framework design, large language models (LLMs), and interactive digital twins with real-world municipal decision-making. The project focuses on deploying auditable, human-in-the-loop AI agents to aid in routine urban operations and emergency response (e.g., severe flooding, power outages, and critical water main failures).
- Agentic AI & Multi-Agent Architecture: Architect, build, and evaluate multi-agent systems powered by LLMs and machine learning, incorporating Orchestrator and Memory agents, vector databases, and knowledge graphs to enable complex goal planning and scenario execution.
- Natural-Language Interaction & Workflows: Develop conversational, human-in-the-loop interfaces that allow domain experts and non-technical stakeholders to query real-time data, execute complex simulations, and run "what-if" analyses using natural language.
- System & Simulation Integration: Integrate legacy utility documentation, real-time sensor streams, and domain-specific engineering/mechanics modeling tools into a unified AI-driven digital twin testbed.
- AI Safety & Privacy Execution: Implement secure-by-design agentic architectures, including sandboxing, tenant isolation, and audit logging to safely handle sensitive municipal and utility infrastructure data.
- Pilot Execution & Translation: Collaborate with computer scientists, civil engineers, and operational partners from the City of Detroit and the Great Lakes Water Authority (GLWA) to run and validate real-world pilot exercises.
- Research Dissemination: Lead the authoring of high-impact journal articles on agentic AI frameworks, present at premier AI and computational engineering conferences, and contribute to center-scale extramural grant proposals.
- Ph.D. in Civil/Infrastructure Engineering (with an AI focus), Artificial Intelligence, Computational Engineering, or a closely related field.
- Strong expertise in Agentic AI & LLM Systems: Demonstrated experience designing, building, and deploying multi-agent architectures, tool-using AI agents, or retrieval-augmented generation (RAG) systems.
- Advanced Technical Skills: High proficiency in Python and modern AI/LLM orchestration frameworks (e.g., LangChain, AutoGen, CrewAI, LlamaIndex, PyTorch, or vector databases).
- Strict Two-Year Commitment: Ability to commit to a minimum two-year appointment.
- Strong collaboration and communication skills, with the ability to bridge computer science concepts with domain engineering and municipal applications.
- Experience with human-in-the-loop systems, interactive simulation environments, or digital twin platforms.
- Working knowledge or background in mechanics, infrastructure systems, hydrodynamics, or urban asset management.
- Experience with enterprise AI security, sandboxing, or privacy-preserving machine learning.
- Track record of working in multidisciplinary teams or collaborating with public sector/industry partners.
Term length
Due to the structured phases and pilot execution timelines of this initiative, this position requires a minimum two-year commitment. The initial appointment is for a one-year term with the expectation of a one-year extension, contingent on performance and funding availability. The anticipated start date is between November 1, 2026 to January 1, 2027.
Research Environment
The fellow will be embedded within a rich collaborative network, working under the auspices of the Urban Collaboratory and in close connection with the Michigan Institute for Computational Discovery & Engineering (MICDE).
- World-Class Infrastructure: Access to high-performance computing resources, advanced AI testbeds, and state-of-the-art testing facilities.
- Direct Real-World Impact: Leverage existing data-sharing cooperation with Detroit and GLWA to deploy and test agentic AI systems in active municipal contexts.
- Interdisciplinary Ecosystem: Collaborate across top-ranked departments in engineering, computer science, public policy, and information sciences.
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.
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.
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.
