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method, can engineer thousands of defined mutations in parallel in a single test tube in yeast. Strains are tagged by DNA barcodes, allowing to efficiently track mutations in cell populations during
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visual representation and analysis of large-scale 2D/3D scientific data. This position resides in the Data Visualization Group in the Data and AI Systems Section, Computer Science and Mathematics Division
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. Strong background in numerical linear algebra, algorithm design, and parallel computing. Proficiency in programming languages such as python. Experience with HPC environments and linear algebra
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mission enabler programme under CORC, where other modelling activities will run in parallel to support and be supported by the findings of the digital twin solution. This innovative ambition is shared with
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defined benefit retirement plan, with 8.25% employer matching funds Additional Voluntary Retirement Programs: Tax Sheltered Annuity 403(b) and a Deferred Compensation program 457(b) Flexible spending
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to) SIESTA (www.siesta-project.org) and its TranSIESTA functionality. SIESTA is a multi-purpose first-principles method and program, based on Density Functional Theory, which can be used to describe the atomic
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behavioral paradigms and combined with computational approaches. We are seeking an extremely motivated postdoctoral researcher with background in human or monkey electrophysiology. Studies will include
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theory and numerical methods, with experience in HPC programming (e.g., C++, Python, MPI, OpenMP, CUDA) and parallel computing environments. - Experience in performance analysis, debugging, and deployment
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Lab researches on a variety of computer systems topics including HPC resilience, data center power management, large-scale job scheduling and performance tuning, parallel storage systems and scientific
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Laboratories (LTS5 ), Mr Jackson at the UoE Parallel Computing Centre (EPCC ), Prof. Smirnov from the South African Radio Astronomy Observatory (SARAO ), Dr Akiyama from MIT Haystack Observatory (Haystack ), Dr