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, demographic, lifestyle, laboratory, imaging and longitudinal health data provides opportunities to apply Artificial Intelligence (AI) and Machine Learning (ML) to colorectal cancer research. Research Aim
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of underlying receptor-analyte interactions, and the development of suitable machine learning frameworks for the selection and optimization of receptor combinations for different analytical tasks. Key
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. The increasing availability of electronic health records, clinical measurements, medical imaging and longitudinal health data provides opportunities for Artificial Intelligence (AI) and Machine Learning (ML
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Job description: Are you a researcher in machine learning for speech and audio who wants to develop technology for earlier detection of lung disease? We have an exciting opportunity for a Research
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and machine learning methodology to help deal with key challenges in developing such models in large-scale observational electronic healthcare record data. These models will be applied to important real
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the School of Computer Science at the University of Sheffield, you will lead the machine learning research on acoustic foundation models for respiratory health. You will work with large-scale real-world
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discrete choice modelling, behavioural data science or machine learning? Are you interested in developing the next generation of AI tools that accelerate scientific discovery while maintaining behavioural
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interface of machine learning, deep learning, data science and applications in forest sciences. Together with the Director, you will further develop KIForst as a faculty-wide platform for methodological
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Are you a computer scientist or machine-learning researcher interested in making medical-imaging AI work reliably beyond the dataset on which it was developed? We have an exciting two-year Grade 7
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at developing methodological contributions at the intersection of computer vision, multimodal learning, predictive world models, embodied AI, and human-robot interaction. The candidate will work towards models