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Field
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. Experience in working with large data sets, knowledge of statistics, and some programming expertise is essential. The project is based in ECEHH, at the University of Exeter’s Penryn Campus in Cornwall, and may
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informatics, biomedical engineering, statistics, or related fields. The lab is engaged in developing novel deep learning and AI-based technologies for digital biopsies from medical images and real-world
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fundamentals Strong programming skills in at least one relevant language (e.g., Python, R, Rust, JavaScript) Experience with data analysis, statistical modeling, or machine learning techniques Familiarity with
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, and a structured approach to problem-solving. Additional qualifications Coursework or other experiences with the following subjects are valued: scientific computing, optimization, statistical machine
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deep learning theory, Bayesian statistics, and generative modelling, this work will advance our understanding of both the capabilities and vulnerabilities of modern AI systems. This will have potential
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analyse large datasets such as the Clinical Practice Research Datalink (CPRD) and Hospital Episode Statistics to identify activity related to the treatment of community acquired pneumonia. This will require
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filled The overarching aim of this project is to find synergies between methods and ideas of modern machine learning and of statistical mechanics for the study of stochastic dynamics with application
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analyzing them by conventional and confocal microscopy. Assessment of cellular lignin and suberin deposition patterns. Assessment of transcriptomic responses to water and nutrient limitation. Element spatial
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link . Utrecht University’s Faculty of Geosciences external link studies the Earth: from the Earth’s core to its surface, including man’s spatial and material utilisation of the Earth – always with a
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synergies between methods and ideas of modern machine learning and of statistical mechanics for the study of stochastic dynamics with application to the analysis of time series. In particular, the project