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, behavioral economics, and machine learning, to help policymakers identify and generate evidence on innovative approaches and policy solutions to their most pressing environmental and energy challenges. Job
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the following ones. Exploration of active auditing techniques for large machine learning models, use of reinforcement learning, potential application to recommender systems. The PhD will mainly investigate
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: Develop and implement machine learning algorithms for SOC and SOH estimation. Analyze large datasets from battery systems to improve model accuracy and performance. Conduct research on predictive analytics
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experience in manufacturing systems modeling, simulation (i.e., DES), and digital twins. • Good knowledge and experience in machine learning, reinforcement learning, and AI-based optimization for production
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machine-learning techniques; interpretation of multimodal patterns of brain organisation; collaboration with international partners in alzheimer prevention; contribution to methodological innovation in
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of environmental hydraulics. We seek someone who is “hands-on” and would be excited to contribute to physical model design and construction. The position also carries responsibility for assisting with
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systems at various scales, for example using ab initio electronic structure methods like density-functional theory, developing interatomic potentials with various methodologies including machine learning
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engineering/M2) to have a solid background in applied mathematics, Machine/Deep Learning, in particular generative models (diffusion models, flow matching), as well as in statistical signal/image processing and
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, funded by a Leverhulme Trust Research Leadership Award held by Dr Alessio Spurio Mancini. ECLIPSE's goal is to develop next-generation inference frameworks that combine machine learning with rigorous
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optimization and meta-heuristics; economic paradigms (game theory, mechanism design, electronic markets); agent modeling and simulation; agent planning, scheduling and decision support; agent learning and