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Project Overview This PhD project is part of an Innovate UK-funded research programme focused on developing a novel ammonia-fueled engine and generator set (genset) demonstrator for harbour and marine applications. The successful candidate will work closely with multidisciplinary teams spanning...
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Early and accurate cancer detection remains a critical global healthcare challenge, with profound implications for patient outcomes and treatment strategies. While Time-of-Flight Positron Emission Tomography (ToF-PET) offers vital functional and molecular insights for improved cancer staging,...
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Project summary: A PhD student is sought to undertake a project jointly funded by University of Strathclyde and National Manufacturing Institute Scotland project. The project aims at researching a new sustainable femtosecond laser nanomanufacturing process to overcome the challenges of atomic...
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Exciting Fully Funded PhD Opportunity: Novel Sealing for High-Pressure H2 and Low-Carbon Storage Technologies - Help Shape the Future of Clean Energy Storage! School of Mechanical, Aerospace and Civil Engineering PhD Research Project Directly Funded UK Students Prof R Dwyer-Joyce Application...
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Project details Early detection of cognitive decline allows identification of those at high risk of developing dementia when medical treatments may be effective in preventing disease onset. Our group have developed an AI-enabled system which can extract detailed retinal vasculometry...
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degree or MSc degree (Distinction/Merit) in engineering, computer science, or other closely related fields. Experience with ROS and proficient programming language skills (C++, Python, MATLAB) would be
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) honours degree (or equivalent) in chemistry, physics, materials science, computer science or other related discipline. This 42-month studentship comes with a budget for training, conference attendance as
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background, we welcome applicants from other relevant disciplines, including psychology, sociology, criminology, law, and computer science. This PhD studentship is fully funded for up to 3.5 years with a tax
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with: • Experience with programming (Python, MATLAB), • background in aerospace, computer science, robotics, or electrical engineering graduates, • hands on skills in
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AI-Driven Digital Twin for Predictive Maintenance in Aerospace - In Partnership with Rolls-Royce PhD
relevant field such as engineering, computer science, or applied mathematics. Experience or interest in AI, machine learning, or digital systems is beneficial. We welcome candidates from diverse backgrounds