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Field
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maintain the workload scheduler and architect quality-of-service policies. Administer Linux systems across infrastructure projects and deployment of new GPUs for research and teaching. Troubleshoot complex
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at least two related publications. Proficiency with core HPC programming languages and paradigms, including C/C++, Fortran, and MPI. Proficiency in GPU-accelerated HPC programming, with emphasis on CUDA and
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requirements for developmental programs. Receives a moderate level of guidance to design applications to meet University and business requirements. Performs code testing on components and works to ensure
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or demonstrated skills and qualifications through projects, initiatives, or outstanding performance. Hands-on scripting experience (Bash, Python, or other dynamic language). Unix/Linux programming or system
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in chemistry, physics, or related field. At least 2 years of experience developing quantum Monte Carlo algorithms. Strong problem-solving and analytical skills. Python programming experience. GPU
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Massachusetts Institute of Technology (MIT) | Cambridge, Massachusetts | United States | 29 days ago
research experience; strong proficiency in Python and C++, with deep familiarity with AI/ML frameworks (PyTorch, TensorFlow, JAX); hands-on experience with GPU programming models (e.g., CUDA, HIP, or OpenCL
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Massachusetts Institute of Technology | Cambridge, Massachusetts | United States | about 1 month ago
fields and/or computational research experience; strong proficiency in Python and C++, with deep familiarity with AI/ML frameworks (PyTorch, TensorFlow, JAX); hands-on experience with GPU programming
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Sep 2026 Is the job funded through the EU Research Framework Programme? Other EU programme Is the Job related to staff position within a Research Infrastructure? No Offer Description Opportunity I
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Programme? Not funded by a EU programme Is the Job related to staff position within a Research Infrastructure? No Offer Description L'objectif de cette thèse est donc de concevoir un environnement de
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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 explore