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candidates with a Master's degree in (computational) chemistry, physics, or materials science who are curious about applied machine learning in the natural sciences. Prior machine learning or Python
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arrangements. Are you an ambitious researcher looking for your next challenge with a computational, industry-focussed project? Do you have a PhD in chemistry, physics, biology or materials science? Do you
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Centrum Wiskunde en Informatica (CWI) | Amsterdam, Provincie Noord-Holland | Netherlands | about 2 months ago
mathematics, applied mathematics, computational science, mathematical physics, or a closely related field; a strong background in one or more of the following areas: partial differential equations, inverse
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computational tools spanning stochastic simulation, machine learning, and deep learning, and is carried out in collaboration with mathematicians, physicists, and experimental biology groups internationally
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Applied Mathematics, Computational Mathematics, Computational Science, Physics, Optical Science, Electrical Engineering or a closely related discipline. Preferred Qualifications: Strong experience in one
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position within a Research Infrastructure? No Offer Description Area of research: Scientific / postdoctoral posts Job description: Postdoctoral Researcher – Computational Electron Microscopy and
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electrochemical technologies. Proven experience in computational fluid dynamics (CFD) and/or multi-physics modelling using COMSOL Multiphysics, ANSYS Fluent, or equivalent simulation platforms. Hands-on
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engineering, chemical engineering, electrochemistry, physics, applied mathematics, computational engineering or a related discipline Sound knowledge of numerical modelling and physics-based battery
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-changing careers. Learn more about Sandia at: https://www.sandia.gov *These benefits vary by job classification. What Your Job Will Be Like: Looking to advance the frontiers of research in computational
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of application advanced numerical and experimental methods for simulating fluids and multi-physics including mesh-based methods, spectral methods, and particle-based methods applied to multiphase