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of subjects such as computer vision, Machine Learning, Artificial Intelligence and Kinematics and dynamics. Autonomous systems, Robotics and Automation. Industry 4.0 and Internet-of-Things. Advantageous to have
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of multimodal imaging, including spatial transcriptomics, single cell and large-scale omics data, digital pathology, using cutting-edge AI and machine learning approaches. You will play a critical role in
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for the challenging tasks facing biomedicine and public health. We are seeking a highly motivated Research Associate in Biomedical Machine Learning, who is passionate about advancing machine learning methodologies
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to co-develop tools that are embedded into routine health systems and data dashboards used to guide policy decisions. This role sits at the intersection of generative machine learning, statistical
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machine learning and hardware assurance. The project’s interdisciplinary nature provides a strong foundation for careers in applied research, secure electronics, or further academic study, with real impact
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and enabling commercial deployment. The work will integrate model based design of experiments, machine learning, hybrid and kinetic modelling (digital twin development), process design, simulation and
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in AI research, 1st in the UK for computer vision and top 5 for AI, computer vision, robotics, machine learning and natural language processing (CSRankings) and were 7th in the UK for REF2021 outputs
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the delivery of the school’s learning and teaching outcomes, including working with conventional machine tools/hand tools within an Engineering Machine Shop environment. Ability to use good
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teach at the University of Vienna, where more than 7,500 academics thrive on curiosity in continuous exploration and help us better understand our world. Does this sound like you? Then join our
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malignant precancerous lesions in the mouth. To facilitate the machine learning model building, the virtual oral tissue models will be developed based on knowledge derived from tissue-engineered constructs