156 phd-mathematical-modelling-ecological-modelling Postdoctoral positions at University of Oxford
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renewable award. You will lead a programme of research in the molecular mechanisms of cardiovascular disease, that may include a range of approaches including targeted genetic murine models, primary cell
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with cutting-edge models and technologies—including patient-derived glioblastoma organoids, CRISPR-based screens, mass cytometry, and advanced microscopy—to dissect these complex biological processes
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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
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these bioinformatic experiments. Access to a high-performance computer will be provided. The candidate must be capable of generating complex molecular compound models in silico and using current molecular dynamic
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good understanding of the relevant basic theory, skills in data analysis and numerical modelling, and a strong research track record. Please direct enquiries about the role to: Only applications received
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challenge. We seek a senior computational biologist to apply these extensive in-house datasets toward the development of novel, domain-tailored machine-learning models and analytical methods. You will explore
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team, and independently, are essential. You will also provide guidance to less experienced members of the research group, including postdocs, research assistants, technicians, plus PhD and project
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of the research group, including postdocs, research assistants, technicians, plus PhD and project students. You must have: A relevant PhD/DPhil (or be close to completion), together with relevant experience in
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Machine Learning, Human-Computing Interactions, Social Sciences, and Public Health. Applicants should hold, or be close to completion of, PhD/DPhil with research experience in computer science, statistics
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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