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AI-Driven Digital Twin for Predictive Maintenance in Aerospace – In Partnership with Rolls-Royce PhD
complex engineering data and deliver insights that are robust, adaptable, and applicable across complex, high-value, safety-critical domains. This research will contribute to shaping the next generation of
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for cardiovascular applications. You will build on our group’s expertise on Physics-Informed Machine Learning (PIML), a powerful approach that combines data-driven AI with the rigour of physical and physiological
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You will be collecting, analysing, and presenting data throughout the study informing the intervention and app and contributing directly to the education/instructional videos contained within them
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Department/Location: Department of Engineering, Central Cambridge A position exists, for a Research Assistant/Associate in the Department of Engineering, to work on experimental investigations
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generations of research and development professionals, data specialists, technology experts, inventors, and scientists for industry and society. The Macroscopic Quantum Optics (MQO) Group at the Department
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factors (learning curve). These will be linked with the CCTA imaging biomarker data (quantitative plaque analysis) that is being collected as part of the EU HORIZON TARGET study to determine personalised
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, and materials science, with a strong publication record (h-index 36, i10-index 69). The second supervisor is Dr. Indrat Aria, a materials scientist with expertise in low-dimensional nanomaterials and
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been collected in Malawi under a joint agreement with the Government of Malawi, with field phenotype data, genomic sequencing data obtained in the UK, and micro-CT scanning data being also collected
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Closing Date: 15 August 2025 Eligibility: UK Only Funding: Joint School of Civil Engineering/EPSRC Doctoral Landscape Award Studentship, providing the award of full academic fees, together with a
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technology. Working at the interface between soft robotic engineering and psychological science you will be expected to design and make devices, design and run behavioural experiments and surveys, analyse data