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Field
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willingness to learn: High-performance computing (distributed systems, profiling, performance optimization), Training large AI models (PyTorch/JAX/TensorFlow, parallelization, mixed precision), Data analysis
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Abilities: Experienced in heterogenous computing with GPU accelerators using one of the programming models: CUDA, HIP, SYCL, Kokkos, OpenMP, OpenACC and similar. Familiar with distributed parallel computing
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tight AI-simulation coupling. What is Required: PhD in Physics, Chemistry, Computational Science, Data Science, Computer Science, Applied Mathematics, or a related numerical field. Programming experience
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courses about parallel computing, computer architecture, programming models and high performance computing. These are your qualifications: Must-haves: • Completed doctoral/PhD studies in Computer
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Inria, the French national research institute for the digital sciences | Saint Martin, Midi Pyrenees | France | 2 days ago
friendly and stimulating environment that gathers Professors, Researchers, PhD and Master students all leading research on High-Performance Computing. The city of Grenoble is a student-friendly city
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: Excellent Master or subsequent PhD degree in Computer Science, Mathematics, Physics, or similar fields and industry experience Strong software-engineering fundamentals and hands-on experience with HPC systems
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and/or distributed systems techniques. • Proficiency in programming languages such as Python, C++, or similar, as well as experience with HPC environments and parallel computing. • Demonstrated hands
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Inria, the French national research institute for the digital sciences | Saint Martin, Midi Pyrenees | France | 25 days ago
We welcome candidates with a master (or equivalent title) in computer science, experience with parallel programming, distributed data processing, deep learning or numerical solvers. Expected
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will contribute to areas such as the design and analysis of algorithms (e.g. randomized, quantum, approximation, property testing, online, streaming, sublinear, fine-grained, distributed/parallel) and/or
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distributed intelligence across the computing continuum. In this role, you will have the opportunity to lead and contribute to cutting-edge research aimed at transforming scientific data management and