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computing AI on High-Performance Computing (HPC) cluster. Examples on areas of research interest include but are not limited to: Vision transformers. AI foundation models. Computing and energy-efficient
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and risk assessment modeling. • Prior experience with CCUS research projects. • Familiarity with high-performance computing (HPC) and parallel computing techniques. Required Knowledge, Skills, and/or
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have experience with interactive visualisation of uncertainty (e.g., dashboards, uncertainty mapping). You have experience with HPC or parallel computing for computationally intensive tasks. Our offer A
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Multi-mentor teams (faculty + industry + academic + overseas scholars) with customised career design Access to best national infrastructure (Cryo-TEM, HPC, etc.) Incentives for high performers: extra
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cell RNA-seq, ATAC-seq Experience with python and/or R programming languages, including single cell package ecosystems (scanpy and/or Seurat) Experience working within HPC environments Experience working
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cell RNA-seq, ATAC-seq Experience with python and/or R programming languages, including single cell package ecosystems (scanpy and/or Seurat) Experience working within HPC environments Experience working
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bioinformatic software, writing computer code and working in HPC environments. The University of Oxford is committed to equality and valuing diversity. All applicants will be judged on merit, according
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computing (HPC). This position offers an exciting opportunity to work on cutting-edge research projects at the intersection of numerical linear algebra and advanced HPC. The candidate will join an
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-Performance Computing (HPC) systems are essential infrastructure for solving complex scientific and engineering challenges. However, the rapid growth of HPC alongside AI is creating an urgent sustainability
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results. Machine Learning skills to automise comparison process. Unbiased approach to different theoretical models. Experience in HPC system usage and parallel/distributed computing. Knowledge in GPU-based