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Engineering » Computer engineering Engineering » Control engineering Engineering » Electrical engineering Engineering » Industrial engineering Engineering » Materials engineering Engineering » Mechanical
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to study and predict. In this four-year SNF-funded project, you will develop data-driven, multiscale simulation methods that combine computer simulations, machine learning, and surrogate models to explore
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in Mechanical or Aerospace Engineering, Physics, Computational Science, or a related discipline. The candidates should have: Solid programming skills (Python, MATLAB, or C++). Knowledge of the OpenCV
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of Computational Fluid Dynamics CFD environment and simulations including: - Computation of the microwave field, Coupling of the microwave field with the plasma - Computation of elementary ionization, recombination
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with project partners and disseminate results through reports, visualisations, and scientific publications Your profile You hold an M.Sc. in Data Science, Computer Science, Engineering, Physics
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of the work requires a very high level of experimental skills. You need to program the hybrid printer and possibly modify the device to be able achieve more freedom in printing and milling of the 3D printed SiC
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well as external academic and industry partners. Your profile You are a highly motivated and talented candidate with a Master’s degree in Engineering, Control, Computer Science, Physics, Applied Mathematics, or a
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varied responsibilities in a dynamic, nationally and internationally oriented research environment Access to state-of-the-art experimental and computational infrastructure Attractive employment conditions
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Materials science and technology are our passion. With our cutting-edge research, Empa's around 1,100 employees make essential contributions to the well-being of society for a future worth living. Empa is a research institution of the ETH Domain. The Urban Energy Systems Laboratory...
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Network with 15 funded 3-year PhD positions in parallel. Your profile Master Degree in environmental/natural sciences or engineering, or similar. Experience with developing computational models Preferably