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. Photoacoustic sensing (introductory video: https://youtu.be/2f3V0DQNLYg ) is based on a transformation of absorbed optical energy into ultrasound waves, when a transient optical excitation is used. The optical
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integrate custom AI copilots and conversational agents. Develop, fine-tune, and evaluate LLM-based chatbots and domain-specific AI assistants. Document AI system designs, experiments, code, and processes
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expertise in agent-based modelling. The models we build will have an interface with community stakeholders and mobility service providers, so we are particularly seeking applicants who are comfortable in
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have held a GSI position at U-M, as part of your cover letter, please provide the course title, number, term, and faculty instructor for each course taught. Please also attach a copy of your UM
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have held a GSI position at U-M, as part of your cover letter, please provide the course title, number, term, and faculty instructor for each course taught. Please also attach a copy of your UM
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decision-support environments). Knowledge of network science, knowledge graphs, temporal networks, graph-based modelling, or complex systems; Experience with simulation (e.g., epidemiological spread, agent
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discovery, or scientific knowledge extraction. Experience building or studying autonomous or semi-autonomous coding agents. Experience designing or implementing automated experimentation or simulation-based
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. Experience developing and fine-tuning Large Language Models (LLMs) and transformer-based architectures. Practicalexperience building AI agents, including agentic workflows, autonomous decision-making pipelines
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engineering projects is increasingly complex, particularly when balancing human expertise and Large Language Models as collaborative agents. This project aims to propose a reputation-based agentic Artificial
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support research in: • Transportation systems modeling and simulation, including O/D modeling, multimodal network modeling, agent-based or behavioral modeling • Large-scale computing, cloud-native analytics