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Assistant Professor Position in Transient Electromagnetic Signal Processing, Modelling and Inversion
field data acquisition, processing, and interpretation. * Strong programming skills. Advanced Python programming is mandatory; experience with PyTorch, GPU-implementations, or other high-performance
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topics related to the position. Experience with data management, HPC and GPU is a plus. They should also demonstrate the ability to work effectively in a multicultural, interdisciplinary team at EOS and
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scheduler systems (SLURM). ● Define secure configurations for GPU systems, AI pipelines, high-performance storage systems (GPFS), and research cloud integrations (Azure HIPAA environments
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scheduler systems (SLURM). ● Define secure configurations for GPU systems, AI pipelines, high-performance storage systems (GPFS), and research cloud integrations (Azure HIPAA environments
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software in high-performance computing (HPC) environments. Experience with parallel and accelerated computing frameworks (e.g., OpenMP, MPI) and familiarity with GPUs and large-scale storage systems. Strong
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science for the benefit of humanity. Access to state-of-the-art facilities, including extensive departmental CPU/GPU computing resources and Imperial’s Research Computing Service. A vibrant
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parallel and GPU computing is most desired.PX4, Pixhawk or equivalent. Ability to work well with team members and good communication skills are essential. To apply, please send your cover letter, CV and
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elements will also be taken into account: Programming skills in C, C++ and Java, as well as knowledge of algorithms and data structures, software engineering, parallel computing and GPU programming
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European Molecular Biology Laboratory (EMBL) | Brandenburg an der Havel, Brandenburg | Germany | 2 months ago
biology and in IT, including on-site HPC and GPU farms and multiple channels to scale-out to European supercomputing resources. Collaborative, Interdisciplinary Environment: Thrive within a network of
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, and guidelines to ensure continued relevance and effectiveness. Evaluate incoming resource and procurement requests (e.g. GPU workstations, servers, and cloud credits) in compliance with university