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approaches to couple machine learning potentials with molecular mechanics force fields, and they will investigate the use of machine learning potentials as data sources for training force fields. They will
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contemporary high-resolution next-generation sequencing and array-based genomic and epigenomic datasets across large cohorts of human tumours and experimental models, alongside complex drug screening, efficacy
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hydrodynamics for novel marine vehicles, including large ships and small AUVs and offshore renewable energy systems including offshore wind. You are expected to perform advanced computational fluid dynamics
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(Oxford University) and colleagues from the Children’s Public Health Service in North Tyneside Council. See the ECLS website for more information about the team and the School of Education, Communication
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and play a key role in growing an internationally visible regenerative engineering team. For further information on The School of Engineering, please click here For full details about this vacancy and
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(murray.pollock@ncl.ac.uk ). For further details about School of Mathematics, Statistics and Physics, please click here Full Information about Newcastle University can be found here . We are committed to building
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information or informal enquiries, please contact Dr Matthew Deakin, matthew.deakin@newcastle.ac.uk . The successful applicant may be eligible for a Global Talent Visa under the Endorsed Funder Route
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a tight-knit, collaborative, and supportive environment. We will encourage you to work across our different projects and to supervise PhD and undergraduate students, whilst also giving you the freedom
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the development of research and innovation funding applications. For more information about the Urban Sciences Building, please click here For more information about the School of Computing and our research, please