213 data-"https:"-"https:"-"https:"-"https:"-"https:"-"https:"-"Dr" Postdoctoral positions in United Kingdom
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transcytosis and tropism in both healthy and disease contexts. The work will generate human-relevant data on BBB permeability, receptor expression and transcriptomic signatures that will directly inform AI
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of finding new ways to treat cancer more effectively. Using the data from the lung TRACERx consortium (Jamal-Hanjani et al NEJM 2017; Frankell et al Nature 2023) we have recently experimentally dissected how
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in machine learning and/or computer security and Experience working with LLMs or agent-based systems. Informal enquiries may be addressed to Philip.torr@eng.ox.ac.uk For more information about working
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lead analyses of large-scale datasets, applying advanced computational and statistical methods to integrate multimodal data (including MRI, MEG, EEG, and genomic data). The postholder will work with a
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, including overseeing the research database and preparing reports. You will undertake prediction modelling and/ epidemiological research using population datasets including statistical analyses of the data
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lab has developed the OrthoFinder comparative genomic methods. OrthoFinder has become widely-used in comparative genomics research, it powers many popular databases of online genomic information, and
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Description' for further details on the responsibilities and selection criteria, as well as further information about the university and how to apply. The post is full time for a fixed term until 31st December
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dedicated to ground-breaking multi-disciplinary research in digital and data science, including artificial intelligence (AI). DERI offers an outstanding research environment including a dedicated physical
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lead analyses of large-scale datasets, applying advanced computational and statistical methods to integrate multimodal data (including MRI, MEG, EEG, and genomic data). The postholder will work with a
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immediately until 31st March 2028, with the possibility of extension. The post is part of a Wellcome Trust Collaborative grant ‘Harnessing epidemiological and genomic data for understanding of respiratory virus