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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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the emergence of edge computing, data storage will become more geo-distributed to account for performance or regulatory constraints. One challenge is to maintain an up-to-date view of available content in such a
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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
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skills and qualifications: A recent PhD (completed within the last 5 years) in computer science, electrical engineering, or a related field. Strong background in network interconnect design and
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to well-known open-source projects or a personal portfolio of impactful open-source research code. Experience with large-scale distributed training and high-performance computing (HPC) environments.