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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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Type of award Scholarship Managing department Faculty of Science and Engineering Value The four-year funded A*STAR PhD programme at Manchester enables postgraduate researchers in science and
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start dates: 1 October 2025 (Enrolment open from mid-September) Supervisors: Hari Arora (Biomedical Engineering), Richard Johnston (Materials) and Iain Whitaker (Medicine) Aligned programme of study: PhD
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This self-funded PhD opportunity sits at the intersection of several research domains: multi-modal positioning, navigation and timing (PNT) systems, AI-enhanced data analytics and signal processing
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This PhD project is at the intersection of electromagnetism, numerical methods, and high-performance parallel computing, with application towards the design and optimisation of integrated circuits
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is desirable. This interdisciplinary project is suited for students who wish to gain expertise in both human health and data-driven biology. Please contact Dr Irina Chelysheva (i.chelysheva
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mortality using traditional and new forms of data, with a focus on developing and low-income countries. The successful applicant will spend 18 months at LSHTM and enrol in the PhD programme, with fees funded
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background in biostatistics or data science, and a clear interest in applying these skills to questions of causal inference in longitudinal observational designs. Please note the funding is only available
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the recording of substrate-borne vibrations produced by earthworms (and other invertebrates) in situ. To fully exploit this emerging technology there is a need to unravel the meaning within the data. As such
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This self-funded PhD opportunity focuses on assured multi-domain positioning, navigation, and timing (PNT), integrating data from space-based, terrestrial and platform-based sources of navigation