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Field
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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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, transcriptome and genome analysis software, Linux environment, HPC systems, TopHat, Bowtie, DESeq2, enrichment analysis tools, Genevestigator, psRNATarget, OmicsBox, etc.; experience using public omics databases
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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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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
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and planet formation context Experience in the field with HPC system usage and parallel/distributed computing Knowledge in GPU-based programming would be considered an asset Proven record in publication
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of high-dimensional datasets, and developing bioinformatic pipelines for high-throughput analysis in high-performance computing (HPC) clusters. The work provides the possibility to develop skills in
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local research software engineer for your research group(s) and improve the use of computing among all group members. Stay up to date with the latest HPC, AI, and general computing/data management
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. outside of HPC environments) This post is subject to Disclosure & Barring Service and/or Occupational Health clearances.
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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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-series data of astronomical transients, including gravitational wave data analysis. Experience with high-performance or high throughput computing (HPC/HTC). The initial appointment is for 1 year. It is