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parallel systems " published in the official gazzette BORM 31/10/2025. ( IN SPANISH). Where to apply Website https://convocum.um.es/convocum2/paginas/pin/home.seam Requirements Research FieldAllEducation
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through the EU Research Framework Programme? Horizon Europe - MSCA Is the Job related to staff position within a Research Infrastructure? No Offer Description The PhD student will participate in
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programming tools (e.g. OpenMP, MPI) Accelerator programming (e.g. CUDA, OpenCL, SYCL) Serial and parallel debugging and profiling Parallel numerical algorithms and libraries. System software stack
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Framework Programme? Not funded by a EU programme Is the Job related to staff position within a Research Infrastructure? No Offer Description The candidate will be involved in the collaborative HFSP project
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The University of North Carolina at Chapel Hill | Chapel Hill, North Carolina | United States | 10 days ago
Employment Type: Permanent Staff (EHRA NF) Vacancy ID: NF0009437 Salary Range: Compensation for this position will follow the North Carolina Department of Public Instruction salary schedule found here: https
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Position as Computational Analyst / Bioinformatician in RNA Therapeutics and Cardiometabolic Disease
for identifying protective human gain-of-function gene variants. Supporting the group with (sc/sp) RNA-seq analysis and multi omics integration. Assist with implementation of paralleled microRNA/mRNA single-cell
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Framework Programme? Not funded by a EU programme Is the Job related to staff position within a Research Infrastructure? No Offer Description This post-doctoral position is proposed in the framework of a 48
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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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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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learning, multicore and GPU programming, and highly parallel systems. Good knowledge in one or more of the following programming languages/environments: C/C++, Python, PyTorch (or similar), and Cuda. Place