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sources such as (i) atmospheric models, (ii) satellite remote sensing, (iii) land use information, and (iv) meteorological data. The aim of this PhD is to develop and implement models for integrating data
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, multi-source learning is used to integrate diverse patient populations to build robust models, but having to protect sensitive information. Various modern ML paradigms are proposed to address the diverse
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modalities and populations. This project (SpyGlass) will investigate machine learning methods, particularly generative and foundation models, to discover robust correlation structures in cross-modal datasets
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This project provides an excellent opportunity to develop state-of-the-art mathematical models and computational tools of emerging respiratory pathogens, within a world-renowned research group
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, this interdisciplinary project will couple mathematical models of earthworm movement, stochastic models of the measurement process and designed experiments to improve earthworm detection. Project This project will work
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science; hydrology; climate science; applied physics; applied mathematics. They will use remote sensing techniques and physical modelling to assess climate and glacier evolution in these high research
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Mathematics PhD on the Programme Choice page. You will be prompted to enter details of the studentship in the Funding and Research Details sections of the form. Candidate requirements: Applicants must hold
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analyses, mathematical modelling, or data analysis. But whatever the research approach, the goal would be to influence UK policy that increases protection of the UK population from current or future emerging
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one of the following analysis techniques (multiple preferred): normative modelling, dimensionality reduction techniques, machine learning, deep-learning, state space modelling, advanced statistics
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team tackling major challenges facing the world’s population in global sustainability and wellbeing as part of the QUEX Institute. The joint PhD programme provides a fantastic opportunity for the most