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Location: South Kensington Campus About the role: Applications are invited for the above post to work with Professor Christos Bouganis and his team at Imperial College London for a project funded by the Commission of the European Communities. The successful candidate will be integral to...
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well as access to the group dedicated computing cluster environment with H100, L40s, and A40 GPUs. This post is funded by the UKRI Future Leaders Fellowship, a flexible long-term public funding scheme
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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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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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of GPUs and/or time in either training or inference procedures, which pose considerable challenges to both academia and industry for widespread access and deployment. In particular, the sampling process of
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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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-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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; and scaling and optimising data science and AI research to leverage HPC and GPU infrastructure. Main Duties and Responsibilities 1. Provide leadership of software engineering services managed and
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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
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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