617 phd-in-architecture-landscape-built-environment Postdoctoral positions in United Kingdom
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community. Our University Strategy is built on three pillars of research, education and wider student experience, but also on our keen sense of community and of inspiring others to achieve their potential
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are expected to work as a close-knit team together with three PhD students to create a mutually supportive research environment. Candidates must be enthusiastic about building and working in a large
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support a national and international community of more than 3000 scientists for research into subjects ranging from clean energy and the environment, pharmaceuticals and health care, through
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capable of driving the project forward. The ideal candidate: The ideal candidate will possess (or soon complete) a PhD in Theoretical Physics, Bio-Mathematics or Computational Biology. They will possess a
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Sunday Times Good University Guide 2024. The UWL community is a diverse body of students and staff who work together to create an environment of success and achievement. We celebrate the diversity of our
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Credit and Qualification Framework level 12 (PhD) plus track record of emerging independence within a research/professional environment or alternatively possess professional qualifications and experience
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part in evaluation measures and quality assurance. You take on administrative responsibilities in research and teaching. This is part of your personality: Completed doctoral/PhD studies in the field
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will have a PhD in a relevant area (or be close to completion) and a good understanding of neurotransmission and behaviour. We welcome applicants with experience in some of the following areas and with a
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You will collaborate closely with RCA staff, PhD students, and external partners, contributing to cutting-edge, design-led robotics innovation. Outputs are expected to be published in high-impact
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also have or be close to completing a PhD in any of the following areas as well as the will and commitment to learn relevant topics from the other areas: Statistical and machine learning, mathematical