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We are currently offering a PhD student position focused on developing new methods for molecular engineering that leverage live-cell imaging data and artificial intelligence (AI). The position is a
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sensors and readout electronics, SPECT, PET, and X-ray imaging instrumentations, image and signal processing techniques, pre-clinical and clinical applications. Develop new research areas to include
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, processing, and/or statistical and data analysis tools to analyze multimodal imaging and spectroscopic data. Specifically, the main tasks will involve data collection, management, and analysis, including image
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as possible, and will focus on large-scale cardiac image analytics. Applicants should hold, or be about to obtain, a PhD (or equivalent) in physics, engineering, computer science or applied mathematics
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settings. The project will be supervised by experts in DIC (Hari Arora), surgery (Iain Whitaker) and wider biomaterials imaging research at Swansea University (Richard Johnston), building on decades
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, Hugging Face Experience with Image and/or audio-based AI development Familiarity with research projects productivity timelines Knowledge of the peer review process for research projects and journal articles
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models using frameworks such as PyTorch and TensorFlow. Research experience in medical image analysis using deep learning algorithms. Strong track record in machine learning, computer vision, and medical
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Project Link: PhD Studentship in Artificial Intelligence in Medical Imaging and Diagnostics | Project Opportunities | PhD | University of Leeds Eligibility: UK/International Funding: School of
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procedures. Evaluate CT scans for technical quality, collate processed images in sequence of exposure and appropriately label. Film/transmit to Image Archival System. Schedule patients for procedures; assist