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essentially corresponding knowledge in another way. Experience with Computational Fluid Dynamics (CFD) is advantageous, as is knowledge of quantum chemical calculations (DFT). An interest in machine learning
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and machine learning, will be employed and, if necessary, specifically developed. What do we offer? A creative and inspiring environment full of expertise and curiosity. Karolinska Institutet is one
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methodologies, ranging from material characterization, via machine-learning and high-throughput methods, to ab initio calculation of electrochemical reaction kinetics. The position is part of the Chalmers Area of
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goal oriented and persevering in your work. Candidates will be assessed upon their ability to: acquire knowledge within the fields of control theory, robotics and machine learning, independently pursue
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properties of superconducting circuits, both analytically and numerically. Familiarity with open quantum systems. Background in optimal control methods. Experience with machine learning for optimization