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of its staff . Please visit the links below for additional information about each opportunity. For questions about the research fellowships, awards, or internship, please contact Faye Rosin , director of
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Job Description Job Alerts Link Apply now Job Title: Research Fellow (Quantum Networks) Posting Start Date: 10/06/2025 Job Description: About the Centre for Quantum Technologies (CQT) The Centre
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in adults with cerebral palsy; this project has been funded by NIHR Programme Development Grants. You will conduct a scoping review, recruit and interview participants, analyse qualitative data
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Job Description Job Alerts Link Apply now Job Title: Postdoctoral Fellows (Centre for International Law) Posting Start Date: 22/07/2025 Job Description: Job Description The Centre for International
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, progression, and response to treatments. You will be responsible for the successful design and implementation of the research to the highest academic standards, and to lead on writing up data for publication
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, experimental testing, data analysis) and with a PhD in Psychology or related discipline. The post-holder will join our multidisciplinary research team in the Centre for Innovation for Mental Health, School
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qualitative data, organise a stakeholder event and write up findings of the research in publications and reports. You will be expected to plan and conduct work using approaches or methodologies and techniques
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opportunities to build an international research portfolio. The post holder will work on developing and testing study design and data analysis methods, particularly related to cluster randomised trial designs and
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to their thermodynamic limits, aiming to achieve fully passive refrigeration temperatures. This breakthrough could impact a broad range of applications, including building and vehicle cooling, data centres, biomedical
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structural biology to tackle challenging scientific questions. Your responsibilities will include, but are not limited to: Multi-omics analysis of bulk and single-cell sequencing data. Developing deep learning