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processes associated with CIN [1], leveraging single-cell DNA sequencing understand CIN heterogeneity [2], and development and implementation of machine learning and AI models to imaging data [3]. The student
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members of staff. Research in the Department is organised into six themes : Causality; Computational Statistics and Machine Learning; Economics, Finance and Business; Environmental Statistics; Probability
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integrating Machine Learning (ML) with physics-based degradation modelling will enhance early fault detection, reducing unplanned downtime. This PhD is hosted at Cranfield University, a global leader in
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, and space hardware. This PhD research aims to develop a comprehensive Mode Selection Framework for Reduced Order Modelling (ROM) in Structural Dynamics—using machine learning to build robust
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models, making the use of data-driven approaches a promising direction. This PhD project will investigate the use of data-driven and machine learning approaches, both measurement based but also model based
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marginal structural models will be extended with machine learning techniques for counterfactual prediction and to support sensitivity analyses Candidate The studentship is suited to a candidate with a strong
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, potentially including machine learning. This research will support the path to net zero flights and there will be opportunities to become involved in practical aspects of fuel system design and testing during
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validation with end-users. The student will have access to specialised training in quantum security and advanced machine learning. The self-funded nature of the project affords the unique flexibility to pursue
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considered. Qualifications/Skills PhD degree in a programme relevant to human-computer interaction and/or critical computing, ideally in Computer Science, Industrial Engineering, Interaction Design, or a
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. The successful candidate will develop advanced skills in multi-modal sensor fusion, signal processing, machine learning, and integrity assessment, as well as transferable abilities in critical thinking, project