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-aware learning methods with domain decomposition techniques, enabling parallel training and efficient GPU-supported implementation. Your tasks: Development of physics-aware ML models for 3D blood-flow
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data science courses, soft skill courses and annual retreats) https://www.hds-lee.de/about/ 30 days of annual leave (depending on agreed working time arrangements) and provision for days off between
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related in space and time and to behavioral events. Core Tasks: Getting familiar with the experimental data and the concepts of neuronal coding, and Elephant Analysis of the parallel rate data for
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strong background in applied mathematics Excellent programming skills (Python, C/C++) Good experience in machine learning and parallel computing Good organisational skills and ability to work both
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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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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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procedure, so called observation operators, mapping the model state to the observation space, are essential. Within the project, the direct use of radiance measurements from EarthCARE will be explored by
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(including data science courses, soft skill courses and annual retreats): https://www.hds-lee.de/about/ A qualification that is highly valued in industry 30 days of annual leave and flexible working
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graduate school program (including data science courses, soft skill courses and annual retreats) https://www.hds-lee.de/about/ Further development of your personal strengths, e.g., via a comprehensive
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staff position within a Research Infrastructure? No Offer Description 2 Doctoral Researchers (f/m/d) in Computational and Data Science at KIT https://www.kcds.kit.edu/72.php Application deadline: January