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willingness to learn: High-performance computing (distributed systems, profiling, performance optimization), Training large AI models (PyTorch/JAX/TensorFlow, parallelization, mixed precision), Data analysis
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Max Planck Institute for Gravitational Physics, Potsdam-Golm | Potsdam, Brandenburg | Germany | 2 months ago
, and the LISA Distributed Data Processing Centre (DDPC), where our department plays a leading role in waveform generation and the global fit deep analysis. The institute promotes a healthy work-life
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on the sky. This project is dedicated to resolving the longstanding challenge in geodetic VLBI, which is the systematic error caused by source structure (i.e., angular distribution of the brightness
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that algorithmic parameters are tuned so that the over-approximation of the computed reachable set is small enough to verify a given specification. We will demonstrate our approach not only on ARCH benchmarks, but
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results. Machine Learning skills to automise comparison process. Unbiased approach to different theoretical models. Experience in HPC system usage and parallel/distributed computing. Knowledge in GPU-based
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hydrodynamics and/or N-body simulations in the star and planet formation context Experience in the field with HPC system usage and parallel/distributed computing Knowledge in GPU-based programming would be
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datasets; alternatively, analyse InSAR time-series and GNSS datasets to quantify the distribution of crustal strain and identify potential zones of active faulting Combining structural geology, remote
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institutions, and contribute to advancing knowledge in their respective fields. Program Highlights 1. Duration: Our joint postdoctoral program has a duration of four years, with an equal distribution
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computer science with very good results - Interest on topics around the area of distributed systems and data management - Basic knowledge in distributed systems and graph algorithms is desired - Hand-on experience
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MesaPD to solve complex multiphysics problems. The coupling is done across package boundaries. This also requires more sophisticated approaches in load-balancing. Finally, the newly developed algorithms