56 application-forms-"https:"-"https:"-"https:" PhD positions at University of Nottingham
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able to work independently as well as collaboratively, and be motivated to tackle open-ended research problems. You should hold, or expect to obtain, a first-class or upper second-class (2:1) degree in a
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benefit from access to world-class materials laboratories alongside PEMC’s £18M purpose-built power electronics research facility on Jubilee Campus. The project will also connect to the University’s new
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in biomedical applications by exploiting the capabilities of functional and anatomical ultra-high field MRI in neuroscience. Together, we will support the PhD student in their research and development
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physiological MRI technique development within a translational research environment bridging analytical bioscience and neuro-oncology. Research Environment The successful applicant for a 4-year PhD studentship
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metabolomics and novel physiological MRI technique development within a translational research environment bridging analytical bioscience and neuro-oncology. Research Environment The successful applicant for a 4
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to become an intrinsic part of the global integrated energy system. However, this kind of technology has not yet achieved widespread commercial adoption due to electrochemical systems’ reliability, safety
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multidisciplinary effort to investigate the anatomical, physical and cellular factors that shape internal root environments. The project will explore how root organisation and environmental conditions combine
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facility at Jubilee Campus. The PEMC institute is globally renowned and one of the leading in its field. Who we are looking for We are actively looking for candidates with A first-class (UK equivalent
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are seeking an enthusiastic, self-motivated, and resourceful PhD candidate with a strong interest in sustainable buildings, retrofit, and environmental performance. The successful applicant will be motivated
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autonomous systems with applications spanning aerospace, nuclear engineering, and embodied intelligence. Vision We are seeking a PhD student who is highly motivated to work at the interface of reinforcement