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disciplines: Advanced Computer Science MSc Chemistry MSc by Research Comparative Social Policy MSc Economics for Development MSc Education (Digital and Social Change) MSc Education (Higher Education) MSc Energy
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Leadership online certificate course and the one-week executive programme “Creating Inclusive Organisations”. They will also co-deliver the LSE-UP International Programme on leadership and innovation and help
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financially managing externally funded projects working as part of a programme team and should be able to demonstrate significant knowledge of accounting standards. Candidates with previous experience in higher
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Purpose of role: The Biochar Demonstrator is a £4.5M project funded by BBSRC as part of the £30M Greenhouse Gas Removal (GGR) programme. The Demonstrator will address the uncertainties concerning
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To apply for this role please submit the following document(s): CV Supporting Statement (Your Supporting Statement should be no more than 1000 words and should outline how your skills and experience meet the essential and desirable criteria listed above) You can view your progress and...
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The Role The role focuses on advancing research in explainable and trustworthy machine learning, with a particular emphasis on mechanistic interpretability and its application to healthcare data. The successful candidate will contribute to understanding how modern machine learning models...
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publications, the ability to work well in a multidisciplinary, multi-professional team and hold a corresponding NTN. You will join the NIHR Clinical Integrated Academic Training Programme at the University
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We are recruiting for an exciting research role as a Research Assistant/Data Coordinator, for the Children’s Surgery Outcome Reporting (CSOR) programme. This position is ideal for candidates with
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celebrate their success. We are committed to helping the people who work here to develop through our sector-leading Birmingham Professional programme which provides all professional services staff with
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constitutive relationships directly from data, ensuring both predictive accuracy and interpretability. The project places strong emphasis on rigorous mechanics, inverse modelling, and computational