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- Knowledge and experience with Python, Fortran and/or GPU computing - HPC and parallel libraries such as OpenMP and MPI - HPC parallel IO libraries such as HDF5 or NetCDF - Experience with supercomputer tools
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strong background in applied mathematics Excellent programming skills (Python, C/C++) Good experience in machine learning and parallel computing Good organisational skills and ability to work both
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Professor will be responsible for teaching and research in some of these areas: computer architecture, media, database, algorithms, parallel and distributed systems, etc. Only shortlisted candidates will be
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parallel project into microbial consumption of hydrogen in the subsurface. Both departments are part of the Faculty of Science and Engineering at The University of Manchester, which hosts world-leading
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algorithms in the context of sparse tensor operations and apply them to real-world datasets. Parallel Computing: Explore opportunities for parallelism in the tensor completion process to enhance computational
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computational science, and Fortran itself is a language that is still in active development (last version is from 2023). However, optimizing and parallelizing Fortran codebases remains a challenge, especially
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surrogates or approximators, such as random forests or shallow neural networks, trained to mimic the outputs of the original computations at a fraction of the cost. This hybridization aims not only
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related in space and time and to behavioral events. Core Tasks: Getting familiar with the experimental data and the concepts of neuronal coding, and Elephant Analysis of the parallel rate data for
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/or mixed-methods; no parallel enrollment in another PhD programme; fluent English language skills are a must; knowledge of Bulgarian is an asset; no previous contractual links to the IPS at any point
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accelerators Hardware–software co-design for AI and transformer-based models. Responsibilities Conduct cutting-edge research in parallel computing and AI accelerators Develop and lead externally funded projects