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Field
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device efficiency. There will be an opportunity to learn the tools required for parallel computing using graphical processing units. This will be used to maximise the computational throughput to enable
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the process of solving increasingly complex compute- and data-intensive problems in science and engineering on high-end parallel and distributed computing platforms. The selected candidate will play an integral
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and distributed memory programming tools (e.g. OpenMP, MPI) Accelerator programming (e.g. CUDA, OpenCL, SYCL) Serial and parallel debugging and profiling Parallel numerical algorithms and libraries
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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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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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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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State University of New York University at Albany | Albany, New York | United States | about 12 hours ago
vibration 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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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
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reports to the Director of Advanced Research Computing, Security, and Information Management (ARCSIM) and will help support the needs of the UMaine research community and its collaborators by enabling and