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, GPU) and workshops for mechanical, electrical and electronic development projects. Long-standing and very successful cooperations with industry and clinical partners (cardiology, radiology) offer
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PID2024-155476OB-I00 (internal code J-03493), funded by the State Research Agency. Fuctions to be developed: Expand and improve GPU evaluation tools. Characterize existing GPU architectures in terms
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and developing sustainable engineering solutions. Evaluate and introduce emerging technologies, architectures, and engineering approaches, including HPC, AI/ML, GPU computing, containers, and other
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, networking, and GPU utilization. Help maintain reproducible training recipes, configuration files, launch scripts, and documentation. Work with researchers and CSCS engineers to improve the reliability and
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/SCI Clearance Master’s degree Training and optimizing ML algorithms on GPU hardware architectures, specifically NVIDIA based Working with geo-spatial data Statistics, multivariable calculus, and linear
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LLMs en infraestructuras GPU. - Análisis y evaluación de explicabilidad de las respuestas generadas por la IA generativa Area: Data Science and Natural Language Processing Tasks: - Development
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/ coarse- grained approaches) Experience with enhanced sampling techniques; computational biophysics/chemistry Usage of high-performance computing clusters, preferably GPU-based computing Proficiency in
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take a leading role in the design, deployment, maintenance, and optimisation of large-scale HPC systems, including CPU and GPU clusters, high-performance storage, and advanced networking technologies
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humanity. • Access to state-of-the-art facilities, including extensive departmental CPU/GPU computing resources and Imperial’s Research Computing Service. • A vibrant, interdisciplinary research culture
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candidates hold a Master’s degree in Informatics, Mathematics, or a related field, and possess strong expertise in linear algebra, GPU architectures, and programming in C++ and Python. This is a 100% TVL E13