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, developing solutions for removing and storing greenhouse gases into the built environment, and developing the life cycle assessment method for quantifying multiple cycles of using building products. Your role
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, and dynamic individual who is a team worker, has a positive outlook, and is adaptable and flexible in their working methods. It is also essential that you are highly experienced in setting up continuous
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Research Assistant/Associate in Photonics Integration of Graphene and Related Materials (Fixed Term)
possess sufficient breadth or depth of knowledge in the discipline and of research methods and techniques to work within own area. The candidate will also have the ability to continually update knowledge
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academic performance in undergraduate and, where applicable, Master’s coursework Advanced programming skills in R and Python Familiarity with econometric techniques, especially panel data methods Ability
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used. AI methods for generating regulatory hypotheses between genes, hormones and physical properties will also be developed. Applicants must have/be close to obtaining a PhD or MPhil in Computational
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, working with legacy print, manuscript, and digital sources. You will apply and adapt digital methods (especially TEI XML), analyse provenance data, disambiguate historical agents, and contribute
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used. AI methods for generating regulatory hypotheses between genes, hormones and physical properties will also be developed. Applicants must have/be close to obtaining a PhD or MPhil in Computational
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hold, or be close to completion of, a relevant PhD/DPhil, have relevant experience in the integration of social science methods and ethical analysis and possess sufficient specialist knowledge of ethics
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., product design), or engineering discipline (chemical or biomedical engineering). Experience with qualitative research methods (e.g., ethnography, qualitative interviews, focus groups, or participatory
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reconciliation, enhancement, and integration of the MLGB dataset, working with legacy print, manuscript, and digital sources. You will apply and adapt digital methods (especially TEI XML), analyse provenance data