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Inria, the French national research institute for the digital sciences | Grenoble, Rhone Alpes | France | 13 days ago
of Adrien Taylor and Scott Pesme. The successful candidate will implement and compare different parallel and stochastic numerical optimization paradigms accurately study the selected algorithms, participate
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Inria, the French national research institute for the digital sciences | Villeneuve la Garenne, le de France | France | 13 days ago
contribute to the design, development, and experimental validation of novel graybox tunneling algorithms for multi-objective combinatorial optimization, with a particular focus on their parallelization and
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, including pretrained universal models and models tailored to specific chemical and materials systems. Develop, debug, profile, and optimize scientific codes and workflows on massively parallel computing
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and gene-specific approaches for determining the functional consequences of human genetic variation. Current and developing projects include massively parallel splicing assays, functional
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understanding of parallel application development techniques (parallel programming models, algorithms, and software) Preferred Qualifications: Experience in implementing ab initio simulation codes such as VASP
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grow’. We welcome you to join our community of faculty, students and alumni who are shaping the future of AI, Data Science and Computing. We are seeking a motivated Research Fellow to join the Parallel
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members Sriram Pemmaraju and Sourya Roy on sampling problems in the distributed and parallel computing setting. The ideal candidate will have research experience in sampling algorithms and related areas
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and tuning. Moderate research project experience training large-scale foundation models, especially pipeline/model parallelism. Track record of creating HPC software for numerical methods. Domain
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laser arrays Optimization and acceleration of existing simulation codes Parallel computing and high-performance computing (HPC) GPU acceleration, where appropriate Development of scalable numerical
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are required. Experience in python, Fortran, C++ and parallel computing are a plus. 3. Good publication record in peer-reviewed journals for fluid mechanics. 4. A Ph.D. degree in relevant