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reports Your Profile: Genuine interest in data science and one or more of its application domains: life and medical sciences, earth sciences, energy systems, or material sciences University degree (M.Sc
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, energy systems, or material sciences A Masters degree with a strong academic background in mathematics, computer science, physics, material science, earth science, life science, engineering, or a related
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, earth sciences, energy systems, or material sciences University degree (M.Sc. or equivalent) in applied mathematics or in computational engineering science, computer science, simulation science with a
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interdisciplinary team of engineers, computer scientists, and life scientists Present your work at international conferences and learn about state-of-the-art methods in machine learning, reinforcement learning and
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, train and test novel machine-learning-based solutions on top-tier super-computing hardware Work in an interdisciplinary team of engineers, computer scientists, and life scientists Regularly participate in
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candidate will be considered for integration into the Graduate School “Engineering Covalent Bonds in Molecules and Materials” Ec=m2 (RTG 3082; https://www.uni-saarland.de/forschen/ecm2.html ). For further