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pathways. You will also have the freedom to determine your own research approaches within this broad framework. You will have or be close to the completion of a PhD in statistical/computational genomics with
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and should hold sufficient theoretical and practical knowledge of methodologies such as deep and statistical learning. Informal enquiries may be addressed to Prof. Andrew Zisserman (email
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imaging data, using conventional analyses and machine learning, to provide new evidence of pathogenicity of proteins and pathways across MSK diseases. You will provide bespoke statistical analysis plans
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and collaborate in the preparation of research publications. To be considered you will hold or be close to completion of a PhD/DPhil in Demography, Sociology, Economics, Statistics, Public/Population
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completion of a project. You will hold a PhD degree (or near completion) in a discipline of direct relevance to computational genomics and/or statistical genetics, have the ability to deliver high-quality
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We are seeking an enthusiastic Postdoctoral Research Assistant in Medical Statistics, with an interest in Artificial Intelligence (AI), to join the Computational Health Informatics (CHI) Laboratory
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gene expression. The project will apply a wide variety of bioinformatic and statistical techniques to bulk and single nuclei functional genomic data generated by our teams (e.g., ChIP-seq, RNA-seq, ATAC
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statistical analyses to test specific hypotheses. You will hold a PhD in microbial ecology or in a related subject and have demonstrable experience in conducting fieldwork on the Skokholm wild house mouse
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within the team and lead grant applications on related topics. The suitable candidate must hold a minimum of PhD or an equivalent qualification in computer science, statistics, mathematics, engineering or
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or a related subject) with a keen interest and experience in understanding human learning. You will have excellent statistical, coding and data-handling skills with data from neuroimaging, and the