419 parallel-and-distributed-computing "Multiple" Postdoctoral positions in United Kingdom
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buildings closed days for all full time staff (Part time workers should pro rata this by their FTE). Use our total rewards calculator: https://www.hw.ac.uk/about/work/total-rewards-calculator.htm to see the
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The Opportunity: We are seeking a Postdoctoral Research Associate in Computational Cancer Genomics to join our team at the University of Edinburgh, funded by a Medical Research Council. This is a
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aims to optimize the operations (serving) of AI by developing algorithms that manage compute, network, and storage resources in a carbon-efficient way while supporting long-term benefits
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Are you passionate about taking a lead role in a cutting-edge project at the intersection of genomics, computational biology, and haematological cancer? We have an exciting opportunity for a Senior
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, model predictive control, parallel computing using JAX and rapid online learning, is highly desirable, but candidates demonstrating an ability and willingness to become familiar with these topics and able
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buildings closed days (and Christmas Eve when it falls on a weekday) for all full time staff. Use our total rewards calculator: https://www.hw.ac.uk/about/work/total-rewards-calculator.htm to see the value
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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
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of the land ice contribution to sea level rise until 2300 with machine learning. You will develop probabilistic machine learning “emulators” of multiple ice sheet and glacier models, based on large ensembles
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permeability selection in variant membrane chemistries. This work will run in parallel to experimental analysis conducted at the University of Exeter using synthetic vesicles to observe permeability
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intelligence experts to generate new projections of the land ice contribution to sea level rise until 2300 with machine learning. You will develop probabilistic machine learning “emulators” of multiple ice sheet