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experimental and computational approaches are employed to shine light into key biological processes during the life of parasitic flatworms. Large-scale sequencing datasets (‘omics’) are generated and analyzed
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will have a PhD (or close to completion) in engineering, materials science, physics or other closely-related disciplines. You will be a highly motivated and responsible researcher with strong curiosity
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an opportunity to be involved in analysing the quantitative data collected as part of the project. You will hold a relevant PhD qualification (or be close to completion), with sufficient relevant research
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on qualifications and relevant skills acquired and will also be determined by the funding available. About you Applicants will hold a PhD/DPhil or be near completion of a PhD/DPhil in a subject relative to Structural
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presenting papers and posters will be part of the role. You must hold, or be close to completion of, a relevant PhD/DPhil, together with relevant experience. You will have previous experience of contributing
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will test hypotheses and analyse scientific data from a variety of sources, reviewing and refining working hypotheses as appropriate, develop ideas for generating research income, and present detailed
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technologies have exploded in recent years, generating multi-dimensional data from millions of cells and thousands of molecular features. Understanding these data and harnessing their insights remains an ongoing
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at the intersection of these research areas. You should hold, or be close to completing, a PhD/DPhil in mathematics, statistics, physics, engineering, data science, or a related field. Experience in cancer
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understand the links between maturational accounts of acquisition and the stability of morphosyntactic properties diachronically, with particular reference to French. Acquisitional data will be extracted from
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will be educated to PhD level with relevant experience in molecular plant biology and evolution and will work closely with other group members to assist them with gene functional characterisation