15 computer-programmer-"https:"-"Inserm"-"https:"-"FEUP" Postdoctoral positions at King's College London
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common complex human genetic diseases using genomics and other omics data within large-scale health datasets. The postholder will contribute to objectives and development of a research programme funded by
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Mental Health Younger Generations Programme. You will work with a friendly, supportive, passionate, and hard-working group to undertake statistical analysis of quantitative data to test hypothesis
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to develop a research programme of your own, and apply for independent funding. The postdoctoral researcher will also have teaching opportunities if this is of interest. You will be primarily based
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currently leading the NeuroHand project—a UKRI-funded programme focused on the development of a soft robotic exoskeleton glove for stroke rehabilitation. The role provides an exciting opportunity
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About us The Faculty of Natural, Mathematical & Engineering Sciences (NMES) comprises Chemistry, Engineering, Informatics, Mathematics, and Physics – all departments highly rated in research
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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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programmes involving national and international partnerships, often with our department acting as the lead site in multi-centre collaborations. We have been identified as the leading schizophrenia research
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of Natural, Mathematical & Engineering Sciences (NMES) comprises Chemistry, Engineering, Informatics, Mathematics, and Physics, all departments highly rated in research activities and a wide-ranging portfolio
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. The successful candidate will work within a multidisciplinary team to unravel the metabolic drivers of HCC biology and transplant rejection through cutting-edge spatial multi-omics and computational metabolic
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Hopkins University (USA), and Google Deepmind (London).* About the role The PDRA will lead the development of new computational and mathematical models to quantify and predict infectious disease risk