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Field
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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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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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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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initiatives such as DAISI. Key Responsibilities: Lead an innovative research programme in AI/ML, with applications in medicine, clinical research, omics, imaging, or population health. Translate and implement
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the strategic direction for the unit while personally driving key programs forward. You will own the Center’s research accelerator portfolio - including GPU grants, university partnerships (e.g
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, particularly WES/WGS and RNA-seq datasets. Experience with copy number analysis and/or tumor evolution modeling is a plus. Advanced programming skills for reproducible data analysis in Python or R. Hands
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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
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sciences Collaboration with experts in lab science, medicine, and machine learning Modern GPU compute infrastructure A chance to contribute to cutting-edge research with real-world impact Who you are Strong
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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