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Field
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developing and applying deep learning models, particularly in areas such as natural language processing (e.g. use of LLMs), computer vision (e.g. CNNs for image classification), and multimodal data integration
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Master’s degree in physics, mathematical biology, computational biology or a related subject. They should have good skills in programming languages such as Python, MATLAB or R, and experience in image
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medical image analysis and natural language processing, with applications in cardiology within a global context. You will be responsible for the design and testing of bespoke AI models for cardiac imaging
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will work closely with the Principal Investigator (PI), Co-PI, and the research team to develop deep learning-based computer vision algorithms and software for object detection, classification, and
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Master’s degree in physics, mathematical biology, computational biology or a related subject. They should have good skills in programming languages such as Python, MATLAB or R, and experience in image
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: Statistical signal/image processing, deep learning, machine learning, neuromorphic computing Good communication skills and an appropriate publication record are essential. Solid knowledge of Python and C++ is
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to demonstrate effective and efficient multi-tasking and maintain accurate and up-to-date records. In addition, the applicants should have a high level of proficiency with computer software related to laboratory
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treatment and reducing brain injuries Modern MRI scans tell us about a tumour’s biology. Through advanced computing (radiomics), it is possible to extract much more information from MRI images than is visible
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international collaborations with clinicians, regulators, policymakers, and industry partners. You must have a strong background in machine learning, computer vision, and medical image analysis, with publications
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internationally recognised for its research in craniofacial biomechanics. Located in UCL Mechanical Engineering and supported by state-of-the-art imaging and material characterisation facilities, the lab focuses