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Application Deadline 24 Sep 2025 - 00:00 (UTC) Type of Contract Other Job Status Full-time Is the job funded through the EU Research Framework Programme? Not funded by a EU programme Is the Job related to staff
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Research Fellow (Fusion Shielding Materials) - School of Metallurgy and Materials - 105638 - Grade 7
variety of research methods, such as scientific experimentation, literature reviews. Analyse and interpret data Contribute to developing new models, techniques and methods Disseminating research results
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, specifically modelling burrowing behaviour and its impact on the skull. Responsibilities include conducting a range of computer simulations using discrete element and finite element methods, as
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collaboration with the world-leading Briscoe lab at the Francis Crick Institute. It is using mathematical and machine-learning methods to study the early development of the neural system and developing those
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) Established Researcher (R3) Country United Kingdom Application Deadline 28 Sep 2025 - 00:00 (UTC) Type of Contract Other Job Status Full-time Is the job funded through the EU Research Framework Programme? Not
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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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(STFC, Daresbury), Prof. Jonathan Tennyson (University College London) and Prof Michael Charlton (Swansea). The Research Fellow will work on the development of methods and computer programs adapted
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related work and provide guidance to PhD students where appropriate to the discipline Contribute to developing new models, techniques and methods Undertake management/administration arising from research
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mentoring within GSD’s programmes, particularly through contributing to UCA’s new Master’s in Economic Analysis with Data Science (launching in 2026). This first-of-its-kind programme in the region provides a
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exciting project that will develop new approaches to handle missing data in statistical analyses based on machine learning methods. The Research Fellow will be based in the Department of Medical Statistics