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Field
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scanning confocal microscopy and calcium imaging in time-lapse, computational imaging approaches for analysis of images and movie recordings, analysis of the connectome to identify neural circuits
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This is an exciting PhD opportunity to develop innovative AI and computer vision tools to automate the identification and monitoring of UK pollinators from images and videos. Working at
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Mativenga (UoM), has extensive expertise in laser materials processing. Dr Chu Lun Alex Leung (Mechanical Engineering at UCL) will also collaborate. he specialises in imaging of additive manufacturing and
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Atmospheric rivers are narrow bands of strong vertically integrated water vapour transport (IVT), conjuring the image of a river in the sky. This phenomenon has been studied extensively in relation
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integrating multi-modal data (e.g., time series, geospatial data, text, and image - including both hydrological and human-related data) and capturing complex, non-linear relationships (Bommasani et al., 2021
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high resolution imaging approaches. Determining the role of the UPR-ECM interaction in age-related health in C. elegans, using confocal microscopy, electron microscopy, and physiological and survival
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Project Supervisor - Dr Jonathan Kirby The field of complex numbers is in many ways the most elegant and important example of a mathematical structure in model theory. It has been the prototype
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results from human decision-making to inform the design of this new paradigm, and feed the results of the latter back into human decision-making to help make it more explainable. The PhD student will: (1
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scanning confocal microscopy and calcium imaging in time-lapse, computational imaging approaches for analysis of images and movie recordings, analysis of the connectome to identify neural circuits
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stress analysis, manufacturing, hands-on oriented, digital image correlation, Abaqus, scripting How to apply: Stage 1: Submit your 2-page curriculum vitae (CV), transcripts and a 300-word statement