9 phd-computational-"FEMTO-ST"-"FEMTO-ST" Fellowship research jobs at University of Leeds
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large interdisciplinary team of other PDRAs, PhDs and academic staff, and will collaborate closely with others in the University and elsewhere. You will work to address the challenges of climate change
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is aimed at technical innovations in computer vision and computer graphics (segmentation, registration, tracking and visualisation) to enable real-time interaction for surgical planning and decision
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be invaluable in efforts to conserve biodiversity and improve food security as the climate heats up globally. You should have a PhD (or close to completion) in evolutionary ecology, evo-devo, cell and
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large team with colleagues in Leeds studying other aspects of blood clot structure and function and their influence on thrombosis. You will have a PhD in molecular biology, cell biology, biomedical
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Would you like to be a part of an exciting project to improve circular manufacturing? Do you have a background in robotics? Are you inspired by utilising robotic systems to drive sustainability? As a key member of the Real Robotics Lab, you will lead the development of innovative robotic...
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the ESRC Smart Data Research UK programme (https://www.sdruk.ukri.org/ ). HASP enables high quality, novel and robust research utilising Smart Data. In collaboration with data and delivery partners, it
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interviews. Joining a well-supported interdisciplinary team of ten Centre researchers working on an exciting programme of high-profile research related to policing vulnerabilities, you will play a crucial role
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Grade 7 (£41,064 – £48,822 p.a. depending on experience) This role will be based on the university campus, with scope for it to be undertaken in a hybrid manner. We are also open to discussing flexible working arrangements. Are you an experienced and ambitious researcher looking for your next...
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can support both health and mobility outcomes. The successful candidate would be responsible for the more technical parts of this project, leading the computational modelling of charging infrastructure