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of research computing at LSE. Your expertise will be key in future-proofing our research hardware environment, ensuring high availability, scalability and security across HPC clusters; GPU acceleration, high
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suite of software, and its deployment on the university HPC & GPU based system. The position is primarily research and enterprise, but there would be a contribution of up to 20% to teaching, including
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of code acceleration (GPU) Participate in numerical modelling (HPC (GPU), MPI Fortran / C, C++ Kokkos, Python, Perl) of SAMS front end and physics/test modules. Write research reports, progress reports
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-performance computing, including parallel or GPU programming (MPI, OpenMP, CUDA, Kokkos, etc.) Familiarity with modern software development practices, including debugging, profiling, and version control
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Selectris energy filter, Vitrobot Mk. IV, GPU- and data storage-cluster and ready access to Titan Krioses at the Francis Crick Institute, LonCEN consortium, and the UK national cryoEM facility at eBIC. What
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free text of both biomedical literature and electronic patient records exploiting HPC, including GPUs embedded within NHS infrastructure. Development and deployment of ML operations software and tooling
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showcases and visualisations; and scaling and optimising data science and AI research to leverage HPC and GPU infrastructure. This post is full time and open ended (permanent) Apply online at: Research
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an early member of a friendly, multi-disciplinary team. The project will involve significant coding using the Julia package Molly.jl on both CPU and GPU, as well as addressing relevant computational and
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using the Julia package Molly.jl on both CPU and GPU, as well as addressing relevant computational and algorithmic questions. You will become an expert in molecular dynamics methods and relevant protein
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of our fire modelling suite of software, and its deployment on the university HPC & GPU based system. The position is primarily research and enterprise, but there would be a contribution of up to 20