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regulatory obligations. Hydraulic simulators are physically detailed but computationally slow and calibration-intensive, limiting large-scale scenario exploration and optimisation. Purely data-driven
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these programme link learning directly to the working professional. We believe that this philosophy directly fits with the requirements laid down by apprenticeship standards, serving both apprentice and employer
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Supervisor: Rostislav Mikhaylovskiy Lancaster University is pleased to offer a PhD studentship supported by Green Future Fellowship project: Terahertz magnetic recording for green data storage
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of pre-eclampsia Research area and project description: Pre-eclampsia affects 1 in 10 pregnancies, yet diagnosis remains uncertain. This PhD will integrate clinical data and blood biomarkers to improve
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. Project Description Dynamic assessment of bone and joint motion remains a major challenge in musculoskeletal imaging. While MRI and CT provide high-resolution anatomical information, they are limited in
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for software development and its education. The group is multidisciplinary, including social and computer scientists. We are working with leading industrial partners, such as those within the automotive and
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interoperability is not solely a technical or procedural challenge, but a socio-technical system property shaped by governance, training, information flows, organisational culture and equity considerations
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, (bio)informatics, and multimodal data analysis. The research group focusses on the mechanisms of Hypothalamic-Pituitary-Gonadal (HGP) axis regulation that governs human reproduction. The group
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funded UDLA PhD studentship. The studentship will start on 1st October 2026. Project Description This project develops advanced simultaneous wireless information and power transfer technologies (SWIPT
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closely with project partners (Philippines, Vietnam and University of West London, UK) to analyse results, gather relevant data for modelling, and ensure accurate data collection Analyse data, interpret