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of computer vision and machine learning. Previous experience of real time systems development in Python, OpenCV, PyTorch and deep learning are essential. Experience of C/C++/C#, TensorFlow would be beneficial
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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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that combine deep learning, computer vision, and bioinformatics to extract actionable insights from complex, multi-modal data, including medical imaging, genomics, and clinical records. A central theme of our
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This is a Research Assistant / Research Associate position within a 4-year long project. This position involves the development of novel Computer Vision algorithms for embedding computer vision
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Applicants are invited to apply for a new vacancy at Research Assistant level in Surgical Vision and AI for intraoperative surgical navigation and computer-assisted diagnosis. The post is based
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The overall aim of this project is to develop a real-time monocular vision system for measuring bio test-tube heights in a rack and alignments in the space-defined labware carriage. The vision
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the development and implementation of machine learning (ML), computer vision (CV), large language models (LLMs), and vision-language models (VLM) to automate data extraction and interpretation for productivity
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Oxford’s Department of Orthopaedics (NDORMS) as well as collaborators in Bristol and Cardiff. You should have a PhD/DPhil (or be near completion) in robotics, computer vision, machine learning or a closely
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. This includes the use of multimodal imaging techniques, such as computer vision and hyperspectral imaging, alongside Internet of Things sensors that will continuously monitor critical parameters such as
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rigorous, collaborative research aligned with project goals. Develop and apply deep learning models, particularly in computer vision, NLP, and multimodal systems. Publish in peer-reviewed journals and