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biological insights. A key part of the role will involve teaching and supporting COI researchers in bioinformatics methods, advising on data analysis strategies, and contributing to scientific manuscripts
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prioritise a varied workload, meet tight deadlines and maintain performance under pressure, without close supervision. Attention to detail and a methodical approach to work are crucial. You should have strong
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), to develop systems that improve the efficacy of machine learning-based technologies for healthcare applications. You must hold a PhD (or be near completion) in a field such as AI, computer science, signal
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and realign how we measure and model populations by infusing new types of data, methods and unconventional approaches to tackle the most challenging demographic problems of our time. We are seeking a
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health data, development and testing of solutions using rigorous methods of evaluation recognised in Global Health, and a focus on highly scalable, cost-effective solutions that can be delivered at scale
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learning approaches. You will develop novel, reproducible methods for analysing both structured and unstructured clinical data, generating insights into disease trajectories, predicting clinical outcomes
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methods suitable for legged systems in physically-realistic simulated environments and on real robots. You should hold or be close to completion of a PhD/DPhil in robotics, computer science, machine
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information and advice on best-practice methodologies in machine learning/deep learning. It is essential that you hold a PhD/DPhil (or close to completion) in a relevant quantitative field (e.g. biostatistics
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, available for up to 30 months, tenable immediately, to conclude before May 31st 2028. Intelligent agents have a venerable history in AI: since the 1980s the problem of how to build hardware and/or software
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biology and relevant methods e.g. protein/RNA assays, with an ability to manage your own research and administrative activities is essential. Excellent communication skills, and experience of following