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theoretical modeling of free-electron-driven X-ray photonics. Working closely with experimentalists, the research fellow will lead the study of coherent X-ray emission from free-electron-driven van der Waals
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-driven atomistic modeling and AI-accelerated cheminformatics to join the Otaniemi Center for Atomic-scale Materials Modeling (OCAMM), hosted by the Department of Chemistry and Materials Science (CMAT
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Experience with deep learning frameworks such as PyTorch or TensorFlow Exposure to AI-enabled scientific workflows that couple simulation with data-driven modeling, including emerging approaches involving
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applied research on AI-driven and AI-enhanced industrial energy systems optimization modeling, material flow analysis, and supply chain analysis of industrial commodities and critical materials
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in the research project - “Towards efficient stamp forming of thermoplastic composites through data-driven thermo-mechanical modelling”. Qualifications Applicants should have a doctoral degree or an
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, with expertise in dynamic/data-driven modeling, optimization, Aspen, COMSOL, or CFD b. Techno-economic analysis (TEA) & life-cycle assessment (LCA) for chemical, energy, or biomanufacturing processes
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modeling of free-electron-driven EUV nanophotonics. Working closely with experimentalists, the research fellow will lead the study of generating and manipulating EUV radiation on the nanoscale, towards
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to advance nearshore hydrodynamic modelling by integrating data-driven and physics-based approaches for simulating wave propagation, wave transformation, and wave–current interaction from deep water to shallow
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. 5. Familiarity with scientific machine learning and data-driven modelling.
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-driven mathematical modeling in a transdiagnostic clinical cohort. https://impact-mh.org/awardees/impact-mh/ IMPACT-Y is collecting repeated measures from approximately 2,400 individuals across multiple