72 modal-analysis-artificial-intelligence Postdoctoral positions at University of Oxford
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We are seeking a Postdoctoral Researcher to join our interdisciplinary food system analysis group at the Oxford Martin School. This ambitious project seeks to use large, data-driven integrated
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provide excellent opportunities for interdisciplinary collaborations, and a world-leading environment to pursue transcranial ultrasound stimulation research with a range of neuroimaging modalities. Clinical
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surveys, early universe and gravitational physics. Good programming experience, an enthusiasm for coding and data analysis, and the ability to work in a large collaboration, are particularly relevant
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statistical programming using R and/or Python, with experience in data management, analysis, and visualisation. You must have demonstrated experience working with large-scale biological datasets, preferably
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imaging and spectroscopy. Experience with data analysis or the ability to perform basic biochemical work with proteins and DNA, e.g., fluorescence labelling, enzymatic reactions will be highly rated in
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detailed T-cell phenotyping and functional assays • Conduct mechanistic studies using molecular and cellular immunology techniques • Contribute to data analysis, presentation, and publication
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; • In vivo delivery of first vector in acute MI and evaluation of expression/distribution; • Analysis of response at the level of myocardium (scar and cellular characteristics) are met
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executing research programmes related to different aspects of thymus biology employing informative experimental models and a broad range of analytical platforms, including single cell transcriptomic analysis
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expected to be bioinformatic in nature. Applicants must have a PhD in a relevant subject, experience of macrosynteny analysis and phylogenetic analysis of gene families, and a thorough knowledge of animal
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oriented environment. The post holder must have experience with EEG and should be able to carry out acquisition and analysis of EEG data independently. The post holder must also have a strong statistical