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An exciting opportunity has arisen for a talented computer scientist to join our team as a researcher within the Green Algorithms Initiative in the Department of Public Health and Primary Care, one
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Predictive Control (MPC) algorithms, innovative coalition-formation techniques, and validate these through high-fidelity simulations. You will design, implement and validate innovative data-driven economic
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for AI based algorithms. Research experience in these areas will be highly valued. The successful candidate will also contribute to the formulation and submission of research publications, development
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cohorts. • WP2 will analyse existing data from multiple youth cohorts. All aspects of the project, including the funding proposal, have been and will be coproduced with young people, schools, and
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/ . The post offers an exciting opportunity for conducting internationally leading research on the whole spectrum of novel machine learning algorithms and practical medical imaging applications, aiming
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into the genomics of population structure and speciation in the Malawi cichlid genus Labeotropheus. This post will build on past work in which over 1000 samples of Labeotropheus from multiple species/populations have
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would be doing: Process and analyse large-scale calcium imaging datasets from multisensory experiments, including neural responses from visual and auditory cortices recorded over multiple days Apply and
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from visual and auditory cortices recorded over multiple days Apply and adapt advanced machine learning frameworks (SPARKS and CEBRA) for supervised and unsupervised analysis of high-dimensional neural
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collaborative project that spans multiple continents. You will contribute to the development of new chronobiological analytics on existing data, design experiments to collect novel chronobiological data, engage
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Natural Language Processing (NLP) in the areas of culturally aware NLP or multilingual conversational NLP, and integration of such methods to support language technology in multiple languages