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                Field
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                Science or a closely related field. • You have experience in matrix algorithms, data compression, parallel computing, optimization of advanced applications on parallel and distributed systems. • An excellent 
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                , AMD uProf, or Omniperf. Debugging experience with distributed-memory parallel applications. Experience with containers (Docker, Podman, Shifter or similar) and modern software practices such as Git 
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                future position is in the Research Group Scientific Computing at the Faculty of Computer Science. The research focus of our group is on parallel computing, supercomputing, and performance tuning and 
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                and run-time management of parallel and distributed computer systems. The modeling, analysis and optimization of the extra-functional aspects of these systems, such as performance, power/energy 
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                Deadline 7 Nov 2025 - 23:59 (UTC) Type of Contract Temporary Job Status Full-time Hours Per Week 35 Offer Starting Date 1 Jan 2026 Is the job funded through the EU Research Framework Programme? Not funded by 
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                & Technology and Systems & Networking. The Parallel Computing Systems (PCS) group at the University of Amsterdam performs research on the design, programming and run-time management of parallel and distributed 
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                fundamentals and hands-on experience with HPC systems; parallel/distributed programming and/or solid UNIX skills Proven experience operating Machine Learning (ML) in production. Able to design, automate, and 
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                The Robotic Materials group at ETH Zurich Department of Materials is looking for three postdocs and one PhD for the project funded by ERC Starting Grant : "Distributed Addressable Robotic Material 
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                State University of New York University at Albany | Albany, New York | United States | about 17 hours agovibration isolation). In parallel to the benefits of quantum computing, artificial intelligence and neuromorphic computing seek to emulate the massively parallel, highly efficient computing capacity 
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                programming; Experience programming distributed systems; Experience with parallel and distributed File Systems (e.g., Lustre, GPFS, Ceph) development. Advanced experience with high-performance computing and/or