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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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program generation and optimization Verification, testing and security of software systems Explainability of AI and of software engineering Software for distributed, highly-parallel AI systems Intelligent
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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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to take a full range of routine and complex digital intraoral and extraoral radiographs, including periapical, bitewing, panoramic, occlusal, and lateral images, and cone beam computed tomography scans. Aid
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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 Part of the research engineer's
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Inria, the French national research institute for the digital sciences | Saint Martin, Midi Pyrenees | France | about 2 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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(fastest execution) for a given Tiramisu program, many code optimizations should be applied. Optimizations include vectorization (using hardware vector instructions), parallelization (running loop iterations
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The University of North Carolina at Chapel Hill | Chapel Hill, North Carolina | United States | 24 days ago
and Experience: Distributed parallel training and parameter-efficient tuning. Familiarity with multi-modal foundation models, HITL techniques, and prompt engineering. Experience with LLM fine-tuning
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the Computer Science program at New York University Abu Dhabi, seeks to recruit a research assistant to work on the intersection of compilers and deep learning. Many companies, such as Google, Facebook, and Amazon
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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