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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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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
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Max Planck Institute for Demographic Research (MPIDR) | Rostock, Mecklenburg Vorpommern | Germany | about 1 hour ago
for Demographic Research, Rostock This network focuses on “scientifically motivated engineering” to design, build, and test digital prototypes—such as machine learning models and large language models—that serve as
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the models of excellent international universities with the unique cultural and economic characteristics of Vietnam, to make a breakthrough in Vietnamese higher education and to become a world-class university
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of reproducing aerodynamic loads in real time for physical experiments. The project combines numerical modelling, data-driven methods, and laboratory experimentation to advance next-generation real-time hybrid
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Job Description At DTU Bioengineering, we are developing next-generation immunotherapies powered by AI-driven protein design. We seek a highly motivated Postdoc to join the project “A novel AI
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to Umeå Marine Sciences Centre and the Department of Ecology, Environment and Geoscience, supported by multidisciplinary teams with complementing expertise in marine biology and AI-driven modelling and
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these plants. The post-doc is expected to build upon existing in-house tools and, where applicable, enhance them by means of AI (machine learning) and data-driven methods. These models are aimed to support
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and technologies, and in advancing data-driven risk monitoring approaches for supply chain resilience. The candidate will conduct comprehensive supply chain mapping, modeling, and analysis—integrating