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Optimal Control Theory Strong programming skills in C++/Python/MATLAB Familiarity with parallelization and high performance computing (CPU and GPU friendly code) Experience with Machine Learning, generative
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– from materials design and processing to machining, mainly of metals. Our expertise spans powder metallurgy, electroplating, additive manufacturing, and material removal, combined with advanced
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systems. This PhD project, part of a national initiative, aims to use AI to design and optimize thermal interface materials (TIMs). It combines machine learning, materials informatics, and experiments
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computational costs by orders of magnitude and enabling breakthroughs in drug design and materials science. The position bridges machine learning and molecular science, with opportunities for collaboration
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). Meritorious: It is also an advantage if you have experience with: Machine learning. Coupling algorithms of fluid-structure interaction solvers. Computational aeroacoustics. Swedish is not required
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fluids, flow-induced pattern formation in both simple and complex flows (e.g. flow instabilities, product defects), multiscale analysis, and the application of machine learning techniques. About the
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for Quantum Technology (WACQT, http://wacqt.se ). The core project of the centre is to build a quantum computer based on superconducting circuits. You will be part of the Quantum Computing group in the Quantum