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transport, supply chain and logistics modelling to contribute to the development and use of the MILES (Multimodal Integrated Logistics for Simulation) and MATRA (Multi-Agent Transport Resilience and
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of Distributed Mixture-of-Experts (MoE) and Small Language Models (SLMs) to create autonomous, intent-driven networks. This isn't just about connectivity; it’s about building a collaborative, agentic ecosystem
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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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, abandonment, comments, peer interaction) Formalization of algorithms for orchestrating educational AI agents : Train RL and LLM agents and study multi-objective optimization (mastery, well-being stability) Work
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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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. 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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. You will then develop a procedure to translate these quantified relationships to a predictive agent based model for the investigation of animal movement behaviour under future climate scenarios. We also
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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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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