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Field
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workloads. Conduct research on language front‑end abstractions, mixed‑precision modeling, heterogeneous parallelism, and MLIR-level transformations. HPC System Co‑Design: Work with domain scientists and
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programming language to solve computational problems Awareness of computational infrastructure and its upkeep Ability to work on multiple projects in parallel and set priorities Willingness to provide training
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Python and C/C++. Expertise in ensemble learning (e.g., Random Forests, Gradient Boosting, bagging/stacking frameworks). Hands-on experience with parallel or GPU-based computing (CUDA, OpenCL
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department in its field, running a globally competitive programme of research and teaching. The Botnar Research Centre enables and encourages research and education into the causes of musculoskeletal disease
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adapting large-scale codes developed for parallel computing. Record of excellence in professional achievement, as evidenced by a strong publication record. Demonstrated ability to carry out independent
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parallel screening platform to discover orthogonal protein binders. In addition to carrying out research, the successful candidate will be expected to apply for fellowship funding, contribute to the writing
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-SofT project, the recruited person will: - design novel algorithm for large-scale block-sparse tensor computations that are suited for massively parallel accelerated supercomputers. - investigate the use
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computing software libraries (e.g., Trilinos, MFEM, PETSc, MOOSE). Experience with shared and distributed memory parallel programming models such as OpenMP and MPI. Experience with one more GPU or performance
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in GPU programming one or more parallel computing models, including SYCL, CUDA, HIP, or OpenMP Experience with scientific computing and software development on HPC systems Ability to conduct
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Science, Computer Engineering, or a related field, completed before the fellowship start date. Candidates should demonstrate experience in at least two of the following areas: compilers, parallel programming