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base, the partnership will bring together the University of Oxford’s expertise in statistics, mathematics, engineering and AI with industry scientists. Within the partnership, small research teams will
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Postdoctoral Researcher in Machine Learning of Isomerization in Porous Molecular Framework Materials
broad range of applications. Computational chemistry and Machine Learning increasingly underlies MFM research to search or screen candidate MFMs prior to synthesis. A major drawback when applying
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development. The ideal candidate will have a PhD in a relevant biological subject, together with experience in molecular biology, cell biology and immunology. Familiarity with flow cytometry, vascular biology
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development. The ideal candidate will have a PhD in a relevant biological subject, together with experience in molecular biology, cell biology and immunology. Familiarity with flow cytometry, vascular biology
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Laboratory in the `Digital Innovation Facility¿ at the University of Liverpool. You will possess, or be close to completing, a PhD in Electrical Engineering / Electronics / Computer Science or a relevant
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to study health and disease. Accordingly, almost all of contemporary biological science research is critically dependent on our ability to identify which genes are related in different species. The Kelly
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and science exploitation of the MIGHTEE survey data. The postholder would have the opportunity to identify new discoveries in the data and would be ideally placed to lead the science based on the data
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and PhD students) and openly share expertise knowledge with team members (e.g. Post-docs). Collaborate with other two post-docs working in this research programme, to deliver on project aims. Contribute
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, within the Diabetes, Metabolism, and Inflammation (DMI) Group at the School of Life and Environmental Sciences. You will be a highly motivated individual who is able to work independently and as part of a
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of experimental demonstrators. Education, Qualifications and Experience Essential Criteria Applicants should hold a PhD in Physics or a relevant area of electrical engineering. (Applicants should have submitted