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Field
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massively parallel computing systems, including GPU-accelerated platforms. Develop and maintain scientific software, primarily in Python , using modern practices for software development, testing
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systems, including surrogate modelling, training data design or reduced-order methods Programming experience in C++ (including OpenFOAM solver customisation), Fortran, or GPU computing (CUDA, OpenCL
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mathematics, computational science or a related field. Solid programming skills (e.g. C++ and Python); experience with GPU computing (CUDA), high-performance computing or machine learning is a plus. A
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demonstrate examples of your independence in research. It is also appreciated if you also have some pedagogical experience. Knowledge of and skills in MPI and GPU programming, along with experience
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looking for people who have: Strong desire to work in the public interest. Proficiency in programming languages or tools (e.g., Python, R, SQL) and experience working with large or complex
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peer-reviewed publications, technical reports, open-source software, or equivalent research contributions. Strong programming and software-engineering experience in languages and environments relevant to
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Parallel numerical algorithms GPU computing Strong programming skills are very important. Experience with C/C++, Python, Julia, MATLAB, CUDA, or a comparable scientific-computing environment is desirable
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other x-ray or neutron scattering experiments. Programming, for example use of Python and GitHub. Data analysis, inverse problems and statistical analysis. Mathematical understanding, knowledge of
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programming in C/C++ or Fortran Experience working in HPC Linux environments Experience with GitHub for version control, continuous integration/testing and collaborative codebase management Excellent
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, Biophysics, or a related discipline with experience in biomolecular simulation techniques, and programming/scripting (Bash,Python) Preferred Qualifications The candidate should have demonstrated