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Field
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AI-driven learning technologies on learning outcomes, cognitive development, and mental health. Details: The ideal candidate will have methodological expertise in one of the following areas: multimodal
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into consideration. We are looking for a candidate with a PhD in Electrical Engineering, Engineering Physics, Mathematics, Computer Science, or a related field, with expertise in programming, physical modeling
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and data-driven modelling approaches in representing quality degradation and shelf-life dynamics. Exploratory perspectives on how digital technologies and data-oriented analyses may inform scientific
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of electrochemical effects into numerical and theoretical models describing the flows within LMBs. These flows, driven by magnetohydrodynamic or thermal phenomena, can become unstable and lead to a short circuit of
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, integrate and share your knowledge of (primarily European) regulatory frameworks and the validation and qualification of these models. Sharing and disseminating knowledge: you will develop and manage an
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plants). The associate will develop rigorous, scalable methods—spanning physics-based and data-driven models—for optimal power flow, demand response of flexible loads, transient/stability-aware dispatch
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one or more of the following: Knowledge graph construction, querying, or reasoning Ontology engineering and semantic modeling Retrieval-Augmented Generation or knowledge grounding Fine-tuning
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challenging due to the complexity of the materials and the various environmental factors involved. The ConSOLIDATe (Controlled Study Of Light Induced Degradation by Advancing Technology) project aims to tackle
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qualities You have a PhD in a computational field such as Artificial Intelligence, Computer Science or Software Engineering for Artificial Intelligence. You have a strong technical background in
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Massachusetts Institute of Technology (MIT) | Cambridge, Massachusetts | United States | about 2 months ago
will work Christopher Knittel (Sloan School of Management and CEEPR). The project will develop empirical models of supply, demand, and international trade conditions for minerals required for the energy