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accelerators originally designed for artificial intelligence. These accelerators achieve exceptional performance by using low precision arithmetic, which is sufficient for machine learning tasks but much too
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of bacteria in the human gut, in-depth work with next-generation as well as 3rd generation sequencing technologies, then this PhD will be right for you. The ideal candidate will enjoy learning about metagenomic
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syndrome. Targeted projects currently include the following: Use AI/machine learning approaches to develop a means to quantify and classify tic movements and vocalisations in Tourette syndrome/tic disorder
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avenues may include linking plankton size patterns to krill dynamics, carbon export or nutritional quality, or developing tools for rapid ecosystem monitoring using machine-learning approaches
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erosion and subsequent effect on land-to-lake dynamics using isotope tracer and source apportionment methodology at test sites in the Winam Gulf. (2) Explore use of remote sensing data and machine learning
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overuse injuries. Wearable sensors to quantify of the impact and benefit of sleep on the recovery, performance and overall wellbeing of athletes. Using big data and machine learning methods to identify
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personalised, ethnically-stratified risk scores. This is a highly interdisciplinary project at the intersection of machine learning, health equity, and precision medicine. The successful candidate will join a
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About Us The applicant will join the new Wellcome-funded Imaging Machine learning And Genetics in Neurodevelopment (IMAGINE) lab, in the Research Department of Biomedical Computing. The post will
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Software Development: Building the Next-Generation Trust Maturity Model Integrating DevOps practices into ML-driven systems: A Framework and Maturity Model for Continuous Machine Learning Development
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for complex data accessible to the scientific community and to produce innovative methodology related to trial designs, longitudinal and event history data, precision medicine, causal inference, AI/machine