637 parallel-and-distributed-computing-phd-"Multiple" Postdoctoral positions in United Kingdom
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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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you will manage your own academic research and administrative activities which involves small-scale project management, to coordinate multiple aspects of work to meet deadlines. You will adapt existing
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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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computational workflows on a high-performance cluster. You will test hypotheses using data from multiple sources, refining your approach as needed. The role also involves close collaboration with colleagues
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for this post. The successful candidate will be required to develop a personal research programme in theoretical cosmology (which may include numerical modelling and/or data analysis), interacting with faculty
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, receiving mentoring, training on large-scale computing, or possibilities of mentoring PhD/MSc students and teaching, if that is what you are looking for Opportunity to work in Finland, which is a safe
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project, an ambitious programme developing medical-grade nanoneedle bandages to deliver life-changing gene therapy for patients with recessive dystrophic epidermolysis bullosa (RDEB). This is a unique
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work make a real-world impact? King’s College London is seeking a talented Postdoctoral Research Associate to join the pioneering NanoCure project, an ambitious programme developing medical-grade
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multiple demands, and able to provide informed recommendations to project leads. Their responsibilities will include engaging and enrolling London schools in the study, collaborating with PPIE groups
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hepatitis and liver disease. This post is funded by the National Institute for Health and Care Research (NIHR) as part of a significant research programme that leverages large-scale healthcare datasets