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(parallelization, efficient data structures), numerical testing, and results analysis. Familiarity with numerical methods, scientific programming in C++, and an interest in reservoir engineering problems
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the delivery of a mesh generation project, funded under a recent major £7m EPSRC Programme Grant REMODEL: Advancing Parallel Mesh Generation and Geometry Representation to Enable Industrially Relevant
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National Aeronautics and Space Administration (NASA) | Greenbelt, Maryland | United States | about 4 hours ago
Postdoctoral Program website for application instructions and requirements: How to Apply | NASA Postdoctoral Program (orau.org) A complete application to the NASA Postdoctoral Program includes: Research proposal
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Sheffield to enable massively parallel processing of ABMs on NVIDIA graphics processing units (GPUs), without the need for specialist understanding of GPU programming or optimisation. This project will
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) experience in code development with parallel programming techniques using the message passing interface (MPI) library Proficiency in writing code with C, C++ and/or Python Ability to demonstrate strong written
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of central London. For more information: https://www.kcl.ac.uk/engineering About the role This role will support the delivery of a mesh generation project, funded under a recent major £7m EPSRC Programme Grant
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of central London. For more information: https://www.kcl.ac.uk/engineering About the role This role will support the delivery of a mesh generation project, funded under a recent major £7m EPSRC Programme Grant
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Framework Programme? Not funded by a EU programme Is the Job related to staff position within a Research Infrastructure? No Offer Description Within the framework of the ANR-TRANSPLAST project
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Science (Ref: FST241110) Job Description Candidates with expertise in one or more of the following areas: Database Management Systems, Programming Languages, Machine Learning, Data Mining, Data Processing
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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