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(coordination) and safety constraints can be intractable. Your work will bridge this gap by providing generalizable, provable design approach that apply across a wide range of networked systems. This 3.5-year PhD
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contributing to better hazard and risk assessments for decision-makers. This PhD will be part of a broader five-year project funded through the MBIE Endeavor Research Programme, titled, “Hazard, risk and impact
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PhD studentship - Protecting Little Ones: Preventing and Reducing Intestinal Infectious Disease in Nurseries using Mixed Methods Award Summary 100% of home fees, minimum tax-free living allowance
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AI-Driven Digital Twin for Predictive Maintenance in Aerospace – In Partnership with Rolls-Royce PhD
Fully funded PhD at Cranfield University, supported by the EPSRC DTP and Rolls-Royce. This 3-year project covers tuition fees, a tax-free stipend, and funding for training, conferences, and a
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Supervisor details: Lead Supervisor Dr Christos H. Halios, c.halios@reading.ac.uk , School of Built Environment Co-supervisors Stefan T. Smith, s.t.smith@reading.ac.uk , School of Built Environment Samuele Lo Piano, samuele.lo.piano@pg.edu.pl , Politechnica Gdanska s.lopiano@reading.ac.uk...
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into car cabins (to reduce the exposure of occupants) and the regions where pollutants accumulate (to be avoided by pedestrians and cyclists) need to be minimised. The PhD objective is to study the effects
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This is a fully funded PhD (fees and bursary) in experimental icing research. Fundamental understanding of droplet impact dynamics is integral to icing. The overall aim of this PhD is to use optical
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We are looking for a highly motivated candidate with strong interest in catalysis and hydrogen economy to take up this exciting PhD project. You will collaborate with other postdoctoral researchers
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risk for future cardiac events. This project is in partnership with Liverpool Heart and Chest Hospital (LHCH). The successful PhD candidate will benefit from working with a multidisciplinary team in
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In this PhD project, we will develop and implement approaches for estimating the uncertainty in AI predictions of chemical reactivity, to help strengthen the interaction between human chemists and