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of participating media. In parallel, neural networks will be designed to approximate the resulting radiation fields, enabling significant reductions in computation time without compromising accuracy. The developed
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or distributed computing Experience with GPU/CUDA, C and C++ programming Working knowledge of OpenCL, OpenACC, Python, MPI Preferred Qualifications PhD in Physics, Biophysics, Computer Science, Engineering
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the applicants, in the disciplinary area of the tender, preferably in the scientific areas of Computer Security or Parallel and Distributed Computing and its adequacy to the category of Assistant Professor
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optimize large-scale distributed training frameworks (e.g., data parallelism, tensor parallelism, pipeline parallelism). Develop high-performance inference engines, improving latency, throughput, and memory
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of Stellar Systems' research group and the Department of Astrophysics. Your profile: • You must hold a Doctoral/PhD degree in astronomy/astrophysics with affinity for programming, or in computer
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Positions Country France Application Deadline 15 Oct 2025 - 23:59 (Europe/Paris) Type of Contract Temporary Job Status Full-time Is the job funded through the EU Research Framework Programme? Not funded by a
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), Dedicated HPC solvers (domain decomposition, parallel/distributed computing), Formulation and solution of optimisation problems (automation, optimal structural design). The developments will follow open
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parallel processing, distributed computing, and resource management techniques for efficient resource utilization. Resource Allocation: Oversee the allocation of computational resources, ensuring scalability
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the full workflow. Help push technology forward within a rapidly evolving environment. Profile MSc or PhD in Computational Science, Computer Science, or a related field Experience in software development
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Education and Experience Preferred Qualifications: PhD in Computer Science, engineering, science, Mathematics, Data Science or similar quantitative subject areas. Expert knowledge of HPC systems, best