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Your Job: In this position, you will be an active part of our Simulation and Data Lab for Applied Machine Learning. Within national and European projects, you will drive the development of cutting-edge Machine Learning applications on the Exascale computer JUPITER. Your work will...
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of AI in the analysis part of a lattice QCD calculation by using techniques such as Gaussian Processes. The University has recently invested just over £1 million in a new High Performance Computing (HPC
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, qPCR, digital PCR, amongst others. Sequencing data analysis will be done using data analysis pipelines (Python, R) on the high-performance computing (HPC) infrastructure. About the TOBI lab
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, qPCR, digital PCR, amongst others. Sequencing data analysis will be done using data analysis pipelines (Python, R) on the high-performance computing (HPC) infrastructure. About the TOBI lab
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of models in existing simulation software conducting numerical studies, also on HPC systems Further specific tasks can be tailored to the attitude and interests of the PhD students/postdocs. Requirements
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will also have the opportunity to participate activities in the wider PGR research community within the Zienkiewicz Institute (ZI) for Data, AI and Modelling including HPC training sessions, the ZI
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HPC centers. Dresden, the capital of the State of Saxony, is a city with a beautiful historical city center and offers a high standard of living with high ratings in housing, safety, and healthcare. TUD
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. The chair hosts its own computer cluster and has full access to the high-performance computing infrastructure at ZIH Dresden, one of Germany’s leading HPC centers. Dresden, the capital of the State of Saxony
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to enhance efficiency, power density, and performance in applications such as high-performance computing (HPC) systems and artificial intelligence (AI) accelerators. Responsibilities and qualifications As a
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physics and diagnostics at the York Plasma Institute Computational combustion modelling using High-Performance Computing (HPC) Machine learning techniques for predictive combustion models Research