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Field
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including heterogeneous accelerator devices such as GPUs, DSPs or FPGAs, requiring software to cope with concurrent and parallel synchronous and asynchronous computation. The emergence of connected autonomous
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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 part in the group's
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management, cache optimization, and vectorization techniques. Strong understanding of algorithms and data structures, especially those suitable for parallel processing and distributed computing. Understanding
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signal processing and/or survey datasets. ML & AI techniques and applications. HPC and orchestration of scientific data processing workflows. Parallel computing (GPU & CPU). good software engineering
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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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100%, Zurich, fixed-term We have an open PhD position at the intersection of machine learning, embedded intelligence and human–computer interaction. The project will explore how learning systems can
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information in the laboratory information system, and scanning necessary paperwork into the laboratory information system. Distribute the referred specimens to the appropriate pathologist. 25% Coordinate
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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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programming, parallel computing, and bioinformatic and statistical genetic software packages. Experience in working with genomic and proteomic data available for large extended pedigrees. License
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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