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, and tools used to program, profile, and debug parallel scientific applications and workflows, such as MPI, OpenMP, CUDA, C++, Rust, Python, or Fortran. Knowledge of the Linux environment. Excellent
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linear algebra computations, building software for scientific applications using GPUs (Graphics Processing Unit), multi-threading and parallelism, numerical discretization methods (finite differences
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Research Framework Programme? Not funded by a EU programme Reference Number COMPETE2030-FEDER-00858000 Is the Job related to staff position within a Research Infrastructure? No Offer Description NOTICE
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Application Deadline 4 Feb 2026 - 00:00 (UTC) Type of Contract Permanent Job Status Full-time Is the job funded through the EU Research Framework Programme? Not funded by a EU programme Is the Job related to
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the responsibility for architecting, designing, and developing software application using web technologies, distributed computation and storage frameworks, data collection nodes, and sophisticated
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: The Software Systems Engineer will have the responsibility for architecting, designing, and developing software application using web technologies, distributed computation and storage frameworks, data collection
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, nonlinear dynamical systems, robotics, and formal methods to develop principled models and algorithms for distributed decision-making in complex and uncertain environments. Your research The candidate will
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Commissariat à l'Energie Atomique et aux Energies Alternatives - Groupe | Gif sur Yvette, le de France | France | 2 months ago
2026 Is the job funded through the EU Research Framework Programme? Not funded by a EU programme Is the Job related to staff position within a Research Infrastructure? No Offer Description Effect
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well as community function, to be investigated in parallel. Standard geochemical analyses will be simultaneously performed to investigate interactions between the major nutrient cycles, and their impact on
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vendors, each with their own management interfaces, data formats, and access restrictions. In parallel, AI-driven services are increasingly deployed in a distributed fashion, with inference spread across