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Field
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: This post will contribute to a developing programme of quantitative research on work and well-being, in relation to modern work (flexible working, digitalisation of work, AI), leadership, and entrepreneurship
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for our pioneering research and pride ourselves on our international reputation. We are equal first in the UK for the impact of our Computer Science research, and second for our Electronic Engineering
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Hospital site in Oxford – a friendly, welcoming place of work with an international reputation for excellence. The Department has a substantial research programme, with major funding from Medical Research
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young people from socially disadvantaged backgrounds into a technical career in environmental science. Part of the NERC ‘Opening up the Environment 2026’ work programme, the project seeks to lead and
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the Department of Computer Science at Royal Holloway, University of London. This is a full-time, fixed-term post for one year from September 2026, with some flexibility around the start date. The project seeks
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relevant subject area: Machine Learning, NLP, Computer Vision or related fields. Strong publication record in AI/ML/CV or related areas. Ability to work independently and collaborate across disciplines
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facilities essential for this ambitious research programme. About the role The Spagnoli group in the Centre for Gene Therapy and Regenerative Medicine is seeking to appoint an enthusiastic, highly motivated
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The Role Applications are invited for a Postdoctoral Research Associate position in the Department of Engineering, with a focus on advanced solid oxide fuel cell (SOFC) modelling, three-dimensional combustion and engine simulation, and AI-assisted modelling approaches for hybrid marine...
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About the Role We are seeking a motivated researcher to join a programme investigating how the tumour microenvironment shapes metastatic progression. The role focuses on understanding how anti
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to the development and optimisation of immunological assays, the generation and interpretation of high-quality datasets, and the integration of immunological findings with clinical and computational analyses. The role