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We are seeking a highly motivated postdoctoral researcher to conduct independent research on foundation models for scientific and engineering applications, with an emphasis on training, adaptation
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against falling from heights in working environments. This includes modeling, simulation and design of passive self-locking mechanisms and joints, FEM analysis on mechanical components, CFD analysis of flow
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Skip to main content Recruit Home Open Recruitments Postdoctoral Scholar - Agrivoltaics systems analysis and modeling (JPF03056) Postdoctoral Scholar - Agrivoltaics systems analysis and modeling
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at a fraction of the computational cost. Recently Argonne successfully implemented, AERIS, a state-of-the-art seasonal-to-subseasonal (S2S) weather model AI model. A successful candidate will collaborate
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Zanna, the successful candidate will focus on developing generative machine learning models for complex dynamical systems for probabilistic forecasts. The postdoc will be expected to lead independent
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of Systems and Control, Department of Electrical Engineering, focused on innovative research in Data-driven Modelling and Optimisation for Fast Charging of Lithium-Ion Batteries. About us At the department
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based on an individual-centered spatial analysis approach (geomatics) using AgentBased Modeling to model mobility and its evolution. The postdoctoral researcher will intervene in the second phase
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Inria, the French national research institute for the digital sciences | Montbonnot Saint Martin, Rhone Alpes | France | 9 days ago
of hybrid modeling frameworks for electromobility, combining physical models, graph-based representations, and data-driven approaches. It aims at integrating large-scale mobility data to improve
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operando experiments under electrical, thermal, or mechanical bias to capture real-time defect dynamics. Integrate multimodal datasets and collaborate with AI/ML teams for data fusion, physics-informed model
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We are seeking highly motivated and talented applicants for a 1-year postdoctoral position (with the possibility of 1-2 year extension) in the area of efficient foundation model inference. Join us