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include high-performance computing, middleware and computing systems. Recent relevant research experience to include: Undertaking research in the area of high-performance / distributed / parallel computing
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results. Machine Learning skills to automise comparison process. Unbiased approach to different theoretical models. Experience in HPC system usage and parallel/distributed computing. Knowledge in GPU-based
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and planet formation context Experience in the field with HPC system usage and parallel/distributed computing Knowledge in GPU-based programming would be considered an asset Proven record in publication
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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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part of Helmholtz networks, e.g., HIRSE; https://www.helmholtz-hirse.de and internationally Your Profile: University degree (Master, Diploma) in natural sciences, computer science or engineering PhD in
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, and pitch decks Participate in strategy development for the formation and early growth of a spin-off company Your profile A Master's degree or PhD in Computer Science, Machine Learning, Electrical
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the development of both, the quantum internet and distributed quantum computing. The objectives of this PhD thesis project are: (a) Demonstrate spin-photon entanglement with single colour centres in silicon carbide
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We are looking for a highly motivated candidate to pursue a PhD programme titled "CFD-informed finite element analysis for thermal control in wire-arc directed energy deposition." This research
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You will be working in a larger research and development project in parallel, distributed and heterogeneous computing. The project work can, under certain circumstances, be combined with an internal
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(PCOG) at SnT, headed by Dr. Grégoire Danoy. PCOG specializes in optimization techniques, with a focus on distributed computing and AI-driven solutions PCOG conducts research in parallel computing, search