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Travel ” which examines signal processing and machine learning methods for inferring active travel activities from optical fibre signals. About You Applicants must have an Undergraduate Degree in
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and machine-learning methods (AI/ML) to extract novel biological insights that drive our translational and fundamental research programmes. In addition to your research leadership, you will play a
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groups working on digital health and wellbeing , network science , computational social science , and various topics in machine learning. You will be working in the research group of one of the PIs
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Machine learning/AI based classifiers Proficiency in coding using R and Python and other similar languages High level analytical capability Ability to communicate complex information clearly Informal
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and experience in developing and implementing machine learning/AI solutions using relevant languages and frameworks Informal enquiries can be made to Dr Hazel Wilkinson, Deputy Director IDAI, email
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experience in spatial analysis and/or machine learning methods, and an interest in applying these tools to urban and housing policy questions. The Fellow should demonstrate potential for producing high-quality
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, data sciences, or a related subject, ideally with a focus on utilising large-scale health/biomedical data and the application of advanced data analysis methods such as machine-learning. Equivalent
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will be tailored to your expertise, spanning from hardware design to system-level optimization and control methods. For the AI position, you will develop machine learning models that incorporate physical
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- and time-specific innervation that extends into adolescence. Our lab has used whole-brain tissue clearing, light-sheet imaging, and machine learning to map the spatial and temporal dynamics of serotonin
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population genetics, bioinformatics, computational biology, statistics or probabilistic machine learning and computer science. Experience of working with large genotyping or sequencing data sets A proven