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this, these simulations need to be massively parallelized. The objective of this thesis is to implement and evaluate different contingency parallelization approaches using our group's computational infrastructure
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or field including associated analysis possibly involving statistical or data analytical software. Work across teams and projects, often on a number of parallel and competing tasks. Work with discretion
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evaluation, or a strong willingness to gain hands-on experience. Eagerness to learn HPC concepts, including parallel computing, distributed systems, and optimization. Analytical skills, problem-solving
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plasma. The main methods used are computer simulations for studying dust dynamics and analysing in situ measurements by spacecraft that carry a dust detector on board. We collaborate with researchers in
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We are seeking an experienced and enthusiastic Cloud Engineer to be based at the Institute of Astronomy (www.ast.cam.ac.uk ) in collaboration with the Research Computing Services (www.hpc.cam.ac.uk
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) to organize, manage, and analyze genomic and genome-wide association study datasets using massively parallel computing infrastructure in the Minnesota Supercomputing Institute (MSI) and Google Cloud (50
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requirements. In parallel there’s been an expansion of AI-driven structural biology (e.g. Alphafold, prediction of disease mutations, prediction of molecular interactions). These projects require specialist
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Parallel Systems. We seek individuals who can play a leading role in developing and delivering our programs. You are expected to teach modules in within the Computer Science BSc and MSc curricula, such as
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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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. Design, install, program, configure and maintain new or existing technology systems and services for a diverse customer base within the University community. Serves as a senior level technical support to