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, including machine learning, computer vision, adaptive data modelling, and computational imaging. The objective is to develop state-of-the-art machine learning algorithms for solving ill-posed inverse problems
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research exploring how the brain regulates perceptual and cognitive processes. In this role, you will conduct human studies using behavioural testing and brain imaging techniques to investigate a range of
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, including machine learning, computer vision, adaptive data modelling, and computational imaging. The objective is to develop state-of-the-art machine learning algorithms for solving ill-posed inverse problems
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computing. With extensive experience in medical image analysis, computer vision, and AI systems through collaborations with leading institutions. Key Responsibilities: Conduct advanced research in the areas
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learning-based computer vision algorithms and software for object detection, classification, and segmentation. Key Responsibilities Participate in and manage the research project together with the PI, Co-PI
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the Job related to staff position within a Research Infrastructure? No Offer Description The position is in the Digital Signal Processing and Image Analysis (DSB) research group, Section for Machine
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biomarker collection and MRI imaging. Both the EJS ACT-PD Trial and Initiative are led by Professor Camille Carroll (Newcastle University, Co-Chief investigator) and Professor Thomas Foltynie (UCL, Co-Chief
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Responsibilities: To independently undertake research on data-efficient object detection with key techniques in few-shot learning, transfer learning, image synthesis, etc. To produce research reports and/or
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organoids and co-culture systems. Key Responsibilities & Activities Process patient biopsies/PBMCs, generate single-cell datasets (scRNA/CITE-seq), and identify testable pathways. Validate targets in tissue
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how ageing affects motor unit structure and function in humans, providing a unique opportunity to work with cutting-edge neurophysiological and imaging techniques. The study will examine age-related