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, computational physics, statistical physics, non-equilibrium quantum many-body physics Ideally, experience with neural quantum states or other applications of machine learning methods in many-body physics
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`s degree and PhD in quantum physics, computer science, electrical engineering, mathematics or a related field Experience in quantum computer programming Experience in applying numerical methods and
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develop processes for the purification of hydrogen obtained from diol-based carrier molecules and to evaluate possibilities for the use of electrochemical compression processes. In this PostDoc position you
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to scientists and investigate possible applications of ML in fields like Chemistry, Numerics, Computational Biology, Astrophysics, Heliophysics etc.. You will be involved in all phases of this process. You will
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travel to present at scientific conferences and strengthen inter-lab cooperations Your Profile: University degree (Master) in computer science, physics or a comparable scientific field PhD in one
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Green Deal and the lignite phase-out. Funded by the German Federal Ministry of Education and Research, the project focuses on two central aspects: accelerated technology development and the sustainable
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`s degree in physics, chemistry, materials science, chemical engineering, or related disciplines Extensive knowledge of X-ray methods Knowledge of X-ray reflectivity Experience with vacuum chambers
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Review, update, and consolidate methodologies, including Bayesian methodologies, in the context of material balance evaluation Your Profile: PhD in applied mathematics, computer science, physics, or in
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degree with subsequent PhD in Physics, Chemistry, Material Science or related disciplines Profound knowledge of the structural characterization of matter primarily with neutron and X-ray scattering
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, the European “Green Deal” and the phase-out of lignite. Funded by the German Federal Ministry of Education and Research, the project focuses on two central aspects: accelerating technology development and