47 engineering-computation "https:" "https:" "https:" "https:" "https:" "https:" "ETH Zürich" Postgraduate positions in Germany
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engineering, biotechnology, computational biophysics, bioinformatics, data science, or a closely related discipline with a strong academic record Genuine interest in data-driven and physics-based modeling
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, computer science and earth science/engineering, or a related field Proficiency in at least one programming language (Python, Matlab, R, C++, Julia, …) Good analytical skills with a sound understanding of data
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) in applied mathematics or in computational engineering science, computer science, simulation science with a strong background in applied mathematics Excellent programming skills (Python, C/C++) Good
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domains: life and medical sciences, earth sciences, energy systems, or material sciences University degree (M.Sc. or equivalent) in applied mathematics or in computational engineering science
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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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, computer science, physics, material science, earth science, life science, engineering, or a related field Proficiency in at least one programming language (Python, R, C++, Julia, …) Good analytical skills with a
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software openly with documentation. Your Profile: A Masters degree with a strong academic background in mathematics, computer science and earth science/engineering, or a related field Proficiency in at least
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available in the further tabs (e.g. “Application requirements”). Programme Description The yDiv Graduate School is looking for highly-motivated, international candidates from the Global South to apply
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) conferences Unique HDS-LEE graduate school program (including data science courses, soft skill courses and annual retreats) https://www.hds-lee.de/about/ Qualification that is highly welcome in industry Further
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surrogates or approximators, such as random forests or shallow neural networks, trained to mimic the outputs of the original computations at a fraction of the cost. This hybridization aims not only