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August 2025 Background To create and contribute to the creation of knowledge by undertaking advanced analysis and validation experiments within the MRC BioFlare research programme: Although outcomes in RA
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International travel may be required for this role. Background This post will advance the application of Machine Learning (ML) in weather forecasting and hydrological prediction. The Research Fellow will develop
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: Develop innovative research programmes aligned with IDAI's research themes Propose, plan, and execute research projects under the IDAI banner Contribute to grant writing and project development to secure
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Hospital and University College London. Role Summary Analyse and interpret research findings and support their publication Contribute to generating external funding Develop and make contributions
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Research Fellow (Fusion Shielding Materials) - School of Metallurgy and Materials - 105638 - Grade 7
fusion engineering & advanced materials, the University of Birmingham is working with national fusion programmes worldwide and with the private sector to advance technologies that promise to fulfil
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during the project. There will be opportunity for additional training for the successful applicant with our collaborators to develop a wide range of technical expertise in immunology, neuroscience and
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closely together during the project. There will be opportunity for additional training for the successful applicant with our collaborators to develop a wide range of technical expertise in immunology
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projects involving at least two MDC research groups Initiative in identifying and contacting MDC research groups to jointly develop the proposed project Mobility: The program is open exclusively to external
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Jan. 2026, based in the University of Birmingham UK. This position will use further develop the novel AI/machine-learning (ML) approach in Chen et al. (2022 & 2024, Nature Geoscience ) and apply
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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