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-month embedded role supporting students within the Little Rock School District’s Alternative Learning Environment campuses and the City of Little Rock Summer Youth Program. This position leads
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and research, in and outside academia. The position will specifically focus on Reinforcement Learning for Resource-Constrained Project Scheduling Problem (RCPSP). The Ph.D. candidate will be a member of
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to provide timely, proactive outreach to ensure degree progress and timely graduation using defined learning outcomes. Reinforce and support student degree progress, academic success, and retention in
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integrates research-based motivational strategies designed to encourage persistence, engagement, and independent learning. Motivational strategies are centered around four themes – autonomy, belonging
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on incentives, the Program integrates research-based motivational strategies designed to encourage persistence, engagement, and independent learning. Motivational strategies are centered around four themes
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for optimisation. (3) Machine Learning-based optimisation: implementation of a preliminary optimisation pipeline (e.g., Bayesian optimisation or reinforcement learning) integrated with the simulator to test
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Machine Learning & AI Spring semester: (beginning of January through mid-May) Python Programming for Data Science General Linear Models Deep Learning & AI The Tutor role will include the following
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or reinforcement learning, and good programming skills in Matlab and/or Python. You will have completed an undergraduate degree or MSc in a quantitative discipline. The Humphries’ group (https://www.humphries
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, or similar ML frameworks Experience with large-scale training or inference of LLMs Interest in LLM alignment, reinforcement learning, or generative AI systems Fluency in English; clear communication, problem
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decarbonization, grid modernization, and the integration of distributed and flexible energy resources. Research topics may include—but are not limited to—AI-based grid operation and planning, reinforcement learning