36 phd-position-data-mining Postdoctoral positions at University of London in United Kingdom
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of Spiralian Asymmetric Cell Divisions”. This research position will reveal the mechanisms that drive the evolution of polar lobes during the first asymmetric cell divisions in animals with spiral cleavage. We
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have a PhD and track record in either computer science with specialisation in relevant AI technologies for surrogate modelling, or in Earth or Environmental Science with a strong track record in
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in the ongoing drive to reduce animal use in scientific research. Applicants must hold a PhD in Cell Biology or related discipline and have a track-record of success, as indicated by first-author
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About the Role This Postdoctoral Research Associate (PDRA) position is part of an exciting EPSRC-funded programme, "Enabling Net Zero and the AI Revolution with Ultra-Low Energy 2D Materials and
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You The successful candidate will have a PhD (or soon to be awarded), or equivalent experience which has involved significant practical cell culture, and ideally experience with molecular biology
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dynamic strain and flow fields during flight. Candidates should hold a PhD in a relevant biology or engineering discipline and be competent with numerical simulations. Desirable competencies would include
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Institute (BCI) in London, with an ideal start date of July 2025. About You The successful candidate will be highly-motivated, have a PhD (or close to completion)* in a biological or computational discipline
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treatments. To achieve this, we will develop personalised cardiac models at scale, and update these models over time, using imaging and electrical data collected by collaborators at multiple centres. We
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About the Role A 12 month post-doctoral research assistant position funded by the Barts and the London Charity (BTLC) is available in the laboratory of the laboratory of Professor Stuart McDonald
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quantitative analysis of key descriptive characteristics to identify whether male politicians are as diverse as their female counterparts. You will then analyse this data on descriptive representation against a