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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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About the role: The Costa Laboratory (https://profiles.imperial.ac.uk/t.costa ), in the Department of Life Sciences (https://www.imperial.ac.uk/life-sciences ), Imperial College London, invites
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workflows, FAISS/embedding retrieval, LLM-based parsing, RAG-style pipeline, and GPU/HPC training. Familiarity with 3D data processing or willingness to learn quickly. Publications, thesis work
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fields, applying advanced techniques such as large-scale data processing and GPU-accelerated computing. Access to state-of-the-art research facilities and a new GPU cluster. Collaborative and inclusive
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, proteins, chemical structures, geospatial, oceanographic, or heath record data. Experience in CUDA GPU programming. Experience authoring open-source Python packages in PyPI. Familiarity with RESTful web
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The Costa Laboratory (https://profiles.imperial.ac.uk/t.costa ), in the Department of Life Sciences (https://www.imperial.ac.uk/life-sciences ), Imperial College London, invites applications for a
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NVIDIA GPU nodes. Additionally, The CSM maintains enterprise computing infrastructure consisting of 20+ servers/devices. This includes various storage devices (TrueNAS, Synology), web servers and Windows
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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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. 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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at the interface of computational systems biology and mathematics/statistics with a strong attitude to open research software development. For more information visit http://www.fz-juelich.de/ibg/ibg-1/modsim