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field. Preference will be given to candidates with: Previous experience in machine learning-related aspects of computational neuroscience, specifically with approximate Bayesian inference, and function
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design of experiments methods, based on Bayesian Optimisation. In addition, the team at Cambridge has its own high-throughput and robotics facilities which we use as a testbed in developing new ML methods
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probability, likelihoods and Bayesian analysis. We are also seeking individuals with a strong interest in public health. Key Responsibilities: Develop models that integrate different data types (e.g., serology
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