187 software-engineering-model-driven-engineering-phd-position Postdoctoral research jobs at University of Oxford
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Materials Manufacturing Hub (SCHEMA), and is associated with a project entitled, ‘Hydrogen-driven bio- and chemo-bio-catalysis to unlock diols and carboxylic acids from hydroxymethylfurfural and furfural
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the lead of Prof Daniela Ferreira conducts research using controlled human challenge models to better understand mucosal immunity to respiratory pathogens and inform vaccine development. This position is
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hold a PhD/DPhil or be near completion of a PhD/DPhil in a relevant biological discipline. Good communication and documentation skills, and the ability to work effectively as part of a team are essential
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proteome in heart-specific cell lines and primary tissue. It will utilize disease model systems to characterize unique cell surface signatures for cardiomyocytes, coronary endothelial cells, and fibroblasts
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tomato and pepper as model systems. Work in Oxford will build on our extensive experience in studying bacterial virulence mechanisms and the role of the plant microenvironment in disease development
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approaches including targeted genetic murine models, primary cell culture and analysis, multi-omics and bioinformatics. The biological focus will be on vascular biology, immune cell function and metabolism
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induced by radiotherapy. You will employ a broad range of experimental approaches, including cell line engineering, transcriptional reporter assays, flow cytometry, qRT-PCR, ELISA, and CRISPR-based genetic
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this hydrogen generation model with the ammonia synthesis module. Find out more about the Hayward research and group at: https://www.chem.ox.ac.uk/people/mike-hayward. About you Applicants must hold a
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on qualifications and relevant skills acquired and will also be determined by the funding available. About you You should hold a PhD/DPhil, or be close to completion, of a relevant PhD/DPhil with a proven record of
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an industry partnered project for translational drug discovery. The role will involve analysing large scale omics and spatial datasets from both primary patient samples and advanced in vitro model systems