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records, site logs, image receipt reports, and quality assessments. · Track and report on protocol progress, image processing timelines, and delivery milestones using internal tracking systems and sponsor
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settings Computing experience including manipulation and transfer of large datasets Clear spoken and written communication skills, with proficient computer use and strong interpersonal and influencing
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performance. Assist radiologist with procedure protocoling and performance. Start I.V.s, administer contrast media as directed and per protocol. Evaluate MR scans for technical quality, collate processed images
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and implement innovative image analysis methods to quantify plant characteristics. Collaborate on multidisciplinary projects involving high-throughput phenotyping platforms. Apply machine learning and
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optical communication networks and systems, as well as machine learning, computer vision and compressing digital videos. The Applied Machine Learning (AML) group is part of the Department for Artificial
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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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focus will be on biomechanics, image processing, machine learning (ML), artificial intelligence (AI), and metrology, the student will also contribute to the co-design of cadaver experiments and data
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review related to histopathology image analysis and the application of machine learning in this field, creates reports based on the review, and present them to senior staff. Contributing to prototyping and
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vision, controls, cyber-physical systems and their security, hardware security, and machine learning and their security. The work will include algorithm design, prototype implementation (e.g., in Matlab
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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