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, surface engineering and its effect on flow behavior, geometric dimensioning and tolerancing. Experience with turbomachinery testing procedures, instrumentation and sensor selection, data
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approaches (ML&AI), data-driven approaches, multi-objective and multi-disciplinary optimization, constraint handling methodologies, and systems engineering. Engineering background in energy conversion systems
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automated platform performing experimental materials synthesis and incorporate data from experimental characterization and simulations. We are looking for PhD candidates with a strong analytical
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three years within a highly interdisciplinary project supported by substantial preliminary data. The successful candidate will have opportunities to develop an independent research direction, access
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learning-based systems is considered a strong asset, as is experience with industrial time-series data or process simulators. We expect the candidate to be self-driven, with strong problem-solving
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and osmosis. The imaging data will be used to link molecular level information to electrostatics and mechanics of membranes. Main duties and responsibilities As a PhD Student, you will be expected to
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simulations software such as COMSOL or CST. Characterize samples in the lab. Model experimental data from first principles using Matlab/Python codes. Write scientific publications, file patents, disseminate
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Science, Data Science, Software Engineering, or a similar degree with an academic level equivalent to a two-year master's degree. We offer At EPFL, we believe that people achieve great results when