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Inria, the French national research institute for the digital sciences | Villeneuve la Garenne, le de France | France | 10 days ago
well as to candidates with expertise in parallel and HPC computing combined with a solid understanding of combinatorial optimization. While prior HPC experience is an advantage for candidates from optimization and
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Inria, the French national research institute for the digital sciences | Grenoble, Rhone Alpes | France | 10 days ago
2 Oct 2026 Job Information Organisation/Company Inria, the French national research institute for the digital sciences Research Field Computer science Mathematics Researcher Profile Recognised
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solutions to compelling problems in energy and security. We are seeking a Postdoctoral Research Associate who will support the Science Engagement Section in the National Center for Computational Sciences
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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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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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integration of novel computer architectures for advanced edge computing scenarios. The research involves design space exploration and the implementation of digital systems using FPGAs, with potential for future
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Biological & Life Sciences Division – Postdoc Researcher: AI for Precision Medicine and Therapeutics
, machine learning, programming in C, C++, Python Scripting languages and MATLAB, using a parallel computing environment Bioinformatics, network biology, network medicine, network analytics, AI, ML, DL, LLMs
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2026 - 23:59 (UTC) Country France Type of Contract Temporary Job Status Full-time Hours Per Week 35 Offer Starting Date 10 Jan 2027 Is the job funded through the EU Research Framework Programme? Not
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successful candidate will collaborate with scientists in DIS, Environmental Sciences division and Argonne leadership Computing Facility to further develop the AI foundation models, benchmarking and deploy them
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kernel design, communication–computation trade-offs, or performance modeling on heterogeneous systems. Theory of parallel algorithms — communication lower bounds or work–depth analysis of sparse and graph