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work. Work in a highly cross-functional environment together with specialists in immunology and deep learning Implement newly-released machine learning models on a GPU cluster Contribute to the design of
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scientific software development. Proficiency in C/C++ and Python, with experience in HPC environments (e.g., MPI/OpenMP; GPU experience a plus). Record of peer-reviewed publications appropriate to career stage
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physics, mathematics or any related field. What we offer State of the art on-site high performance/GPU compute facilities Competitive research in an inspiring, world-class environment A wide range of offers
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approaches, the application of meta learning, and the integration of convex optimization layers Increase inference efficiency (e.g., GPU acceleration) and assess the applicability domain of learned algorithms
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-of-the-art GPU and data storage cluster; direct access to a Titan Krios to the LonCEN consortium and the UK national cryo-EM facility at eBIC. By joining the Costa laboratory, you will become part of a
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. Proficiency in Python and either PyTorch or JAX Experience with HPC, GPU is preferred Related Skills and Other Requirements Ability to collaborate on multidisciplinary research in a collegial environment
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Your profile: Preferably a doctoral degree, but MSc are also encouraged to apply Expert knowledge in one or several of the following High Performance Computing GPU computing Array Computing with JAX A
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, production-grade pipeline encompassing scalable video preprocessing, model training, and inference workflows. Implement GPU-accelerated training and inference, standardized evaluation protocols, and
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and or Python required, experience with wireless testbeds desirable, some familiarity with GPU programming desirable (to support collaboration with NVIDIA) Duke is an Equal Opportunity Employer
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GPU-capable, parallelized simulation frameworks. Work closely with experts in HPC and power systems to enhance scalability and computational performance. Disseminate your findings through scientific