26 parallel-computing-numerical-methods Postdoctoral positions at University of London in Uk
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for medicine use before and during pregnancy. This postholder would work primarily on a recently funded programme of work to develop a novel approach to understanding and communicating the Safety of Medicines in
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About the Role You will develop and apply novel computational methods to quantify the societal impact of fundamental science discoveries. Candidates close to completion of their PhD will initially
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computational methods (Efremova et al. Nature Protocols, 2020; Jain et al., Genome Biology). About You PhD in a biological or computational subject and background in working with genomics data. About the School
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project investigating mechanosensing in Diptera. This post will focus on using detailed wing geometry models and kinematic measurements in computational fluid and structural dynamics simulations to recover
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Institute and RiverD International. The successful candidate will adapt existing and develop and test new methods for detecting metastatic lymph nodes based on their molecular signatures as captured by AF and
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will compare the development of annelids and molluscs and combine single-cell transcriptomics with classic embryological approaches and state-of-the-art computational methods. The findings from
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and leading journals, and to undergo additional methods training. About You Educated to doctoral level in political science or a cognate discipline, you will be proficient in quantitative research
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developmental science. The successful candidate will contribute to a major research programme investigating how educational experiences shape mental health from childhood into adulthood. The role involves working
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research into planet formation/protoplanetary discs or the ISM/star formation and may also have some experience in statistical methods and/or machine learning. Dr Winter and QMUL are committed to improving
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related to gravitational wave astronomy. The primary aim will be the development of advanced approaches for computational Bayesian Inference to measure the properties of Compact Binary Coalescence signals