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to the development of digital twin technologies for sCO2 power generation systems. The Centre for Propulsion and Thermal Power Engineering has a key focus and a proven track record on gas turbine performance, gas path
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technology policies and AI-powered threats fundamentally reshape alliance structures and power dynamics. The second track analyses the geoeconomics of AI through a non-zero-sum lens, revealing how resource
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laboratories, industrial-scale deposition systems and unique characterisation facilities. With a strong track record in energy innovation and industry partnerships, the University of Nottingham provides
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rated as ‘world-leading’ or ‘internationally excellent’. This PhD will be based within the Centre for Space Systems and the Resilient PNT research group, both of which have strong track records in
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in AI and machine learning – from classical approaches to large language models. You are proficient in Python and key ML libraries (e.g. scikit-learn, PyTorch, LLM APIs), and you have a track record of
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climate change-resilient infrastructure slopes. This PhD is co-funded and co-supervised by Network Rail. The aim is to enhance understanding of how drainage systems impact slope hydromechanical behaviour
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practices (e.g., Buddhism, you will have a track record of interdisciplinary work at the nexus of artificial intelligence and neuroscience. Experience collecting multi-modal neurophysiological data would be
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to industrial clients such as Boeing, BAE Systems, Rolls-Royce, Meggitt, Thales, MOD, Bombardier, QinetiQ, Thales, Network Rail, Schlumberger and Alstom. Entry requirements Applicants should have a first or
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are seeking outstanding early-career researchers who meet the following criteria: Educational Background: Ph.D. degree from prestigious university. Research Excellence: Proven track record of impactful research
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scientific research by an excellent track record of research outputs and have an ability to work both independently and collaboratively. Excellent written and verbal communication skills, interpersonal skills