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personal journeys and daily activities, often discouraging use. To address this, the project engages directly with PwMD and their carers to co design a fresh concept of wandering safety that protects
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: Imagine a surgeon operating remotely through a robot—what if the network slows at a critical moment? Even tiny delays can risk patient safety. This PhD project develops new AI approaches to predict network
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, many current UV-filter ingredients raise concerns around safety and ecological impact. This PhD project addresses this urgent need by developing bio-inspired sunscreens, drawing on nature’s own solutions
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the wind/renewable energy training and research elements of the CDT programme. Funded by Siemens Energy and EPSRC, this 4 year this PhD studentship, at the University of Strathclyde is in the area of
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Project Description The global transition toward a net-zero economy requires secure and sustainable supplies of critical minerals, with lithium forming the backbone of electric-vehicle batteries and
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at Cranfield University within a supportive, cross-disciplinary environment spanning energy systems engineering, computational modelling, bioinformatics and food safety science. The studentship is funded by
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., statistical modelling, Artificial Intelligence/Machine Learning) Experience in computational biology and bioinformatic analysis Proven ability to write detailed, technically accurate reports on complex research
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) This PhD project aims to define evidence-based, task-specific colour vision requirements for mainline train drivers and other safety-critical rail staff. The research will focus on colour-dependent visual
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system. This project will focus on improving the intake aerodynamic design systems in terms of design optimisation as well as computational modelling. Entry requirements Applicants should have a first or
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detection of chemical and microbial contaminants in rivers. The studentship is funded by the Leverhulme Trust through the Connected Waters Leverhulme Doctoral Programme, which is supporting new research