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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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`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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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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degree in Physics, Materials Science, Computer Science, Data Science, or related fields Proven experience with large language models (LLMs), natural language processing (NLP), and fine-tuning techniques
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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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science, and applied plant research Example reading: Peleke, F. F., Zumkeller, S. M., Gültas, M., Schmitt, A., & Szymański, J. (2024). Deep learning the cis-regulatory code for gene expression in selected
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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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performance and degradation of electrolysis in dependence on different operating modes Your Profile: Completed Master’s degree in chemical engineering, computational engineering, computational mathematics, data
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property prediction, modern artificial intelligence methods, molecular dynamics, and interdisciplinary research, this is your chance to be part of an exciting journey at the forefront of science and
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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