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multimodal data, ultimately uniting rigorous machine learning foundations with biological discovery. Project details This PhD project will contribute to the development of generative models for multimodal data
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PhD Studentship in Aeronautics: How offshore wind farms and clouds interact: Maximising performance with scientific machine learning (AE0078) Start: Between 1 August 2026 and 1 July 2027
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and loss of migration across western Europe. Benefitting from the strong expertise of the supervisory team in stork ecology, movement analysis and spatial models, the project will leverage large
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the rich, unstructured information found in clinical notes and cannot effectively gather data on lifestyle and social determinants of health. This PhD project will pioneer a novel, hybrid AI framework
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21 Oct 2025 Job Information Organisation/Company The Institute of Cancer Research Research Field Biological sciences » Biology Mathematics » Computational mathematics Researcher Profile First Stage
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they affect local and regional flood risk. This PhD project will explore how riverbeds in large tropical systems respond to the pressures of sand mining, and whether disturbed beds recover once mining stops
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Spectrometry Facility at Birmingham; a large, multidisciplinary research team that works together operating the latest state-of-the-art mass spectrometers. The PhD will start with extensive training in the state
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DoS: Professor Sarah Boulton 2nd Supervisor: Dr Martin Stokes 3rd Supervisor: Dr Michael Whitworth, AECOM 4th Supervisor: Dr Joshua Jones, AECOM Applications are invited for a 3.5 years PhD
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research as a doctoral student you will be passionate about using large-scale data to address important questions in cancer research, have strong experience of quantitative analyses, and be a positive
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Applications are invited for a 3.5 years PhD studentship. The studentship will start on 01 October 2026 Project Description Scientific background Biological invasions represent one of the most significant