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The purpose of this post is to provide technical support to the operation of the clinical and research PET scanning activities in the PET Imaging Centre, working as a member of a team of medical physicists
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for further development. Mentor students Job Requirements: Master’s degree in civil engineering or related field At least 1 year of relevant experience in signal processing and machine learning. Good written
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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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82304 for the Epilepsy Navigation (EpiNav™) Software Platform. EpiNav™ provides state-of-the-art computer-assisted support for the planning of stereotactic neurosurgery procedures. It has been in daily
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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