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and corrosion in aqueous CO2-containing environments (such as geothermal systems) is the continuous injection of chemical inhibitors into the process fluid. These inhibitors can function through a
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optimisation/high-value products Project start date: 01 October 2025 Supervisors: Dr Steve Slocombe and Dr Miguel Lurgi Aligned programme of study: PhD in Bioscience
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Application deadline: All year round Research theme: Robotics, Smart Manufacturing How to apply:uom.link/pgr-apply-2425 No. of positions: 1 This 3.5 year PhD is funded by the Department
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either of these species is likely to affect its onward behaviour, and data on these processes will support predictive modelling. The PhD student will be a part of the Surrey/AWE Centre of Excellence in
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PhD Studentship: Artificial Intelligence for Building Performance – Optimising Low-Pressure Airtightness Testing Supervisors: Dr Christopher Wood (Faculty of Engineering) and Dr Grazziela Figueredo
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This PhD opportunity at Cranfield University explores how next-generation AI models can be embedded within resource-constrained electronic systems to enable intelligent, real-time performance
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outputs for publication in medical journals. Master cutting-edge laboratory assessments of health and imaging using 3 Tesla MRI scanning to investigate skeletal muscle and energy metabolism biomarkers
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are increasingly using self -funded services via pharmacies, getting both medicines and health advice to treat common infections without seeing a doctor. The vast “smart data” that these interactions are producing
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This PhD project will focus on the development of scalable and sustainable dielectric deposition processes tailored for WBG semiconductors, with an emphasis on interface engineering to optimise
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Eligibility: Home students only | Minimum 2:1 in a relevant discipline Stipend: Home students only | £20780 + £2500 industry top up (per annum (tax free)) Overview This exciting, fully-funded PhD opportunity