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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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of AI models and HPC applications, focusing on GPU-enabled computing. Implement parallel processing, distributed computing, and resource management techniques for efficient job execution. Integration and
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Research theme: Control Engineering, Robotics How to apply: https://uom.link/pgr-apply-2425 UK only This 3.5-year PhD studentship is open to Home (UK) applicants. The successful candidate will
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, conducting performance assessments and benchmarking case studies, and helping codes to transition into the era of accelerate compute. You will be embedded into the SHAREing (https://shareing-dri.github.io
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Inria, the French national research institute for the digital sciences | Saint Martin, Midi Pyrenees | France | 3 months ago
. Where to apply Website https://jobs.inria.fr/public/classic/en/offres/2025-09447 Requirements Skills/Qualifications Expected skills include Knowledge on distributed, parallel computing and numerical
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will develop high-performance quantum software technologies, with a focus on quantum compilers, scheduling and orchestration on parallel computing systems, including in distributed quantum computing
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remains an active subject-matter expert in HPC frameworks, distributed computing, AI-accelerated software stacks, and large-scale workflow orchestration. The role supports faculty, research staff, and
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integration with classical HPC; accelerator platforms and accelerated computing; parallel, distributed, and HPC programming models and languages; software design, verification, and optimization; energy
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environments, token-based data-access infrastructures, and next-generation HTTP/S caching technologies. The Lab also maintains the ATLAS distributed analytics and AI-assisted observability and operations
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languages (e.g. C/Fortran) Shared and distributed memory programming tools (e.g. OpenMP, MPI) Accelerator programming (e.g. CUDA, OpenCL, SYCL) Serial and parallel debugging and profiling Parallel numerical