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generative modelling, and graph neural networks. Additional responsibilities include developing research objectives and proposals; presentations and publications; assisting with teaching; liaising and
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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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modern Bayesian modelling frameworks such as Stan, Turing.jl, and PyMC, including automatic differentiation frameworks, MCMC sampling algorithms, and iterative Bayesian modelling. Special attention will be
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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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for Research Fellowship/Career Development Awards from research councils or other funders, or a faculty position during their tenure. Find out more about the fellowship on our website: https
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if information is inaccurate or out of date the right of data portability (to obtain and reuse your personal data) the right to object to networx and the controller and processors handling of your personal data
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leading the PPIE activities across a range of active projects within the group. At the moment, the role will include coordination of the PPIE activities within the new Cancer Data Driven Detection (CD3
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touch with the student experience and informed about life at Catz, in all its variety, and solicit funds and regular giving to support our ongoing charitable and educational objectives. What the Role
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to register an account with our recruitment system (if you have not already) and apply online. Please notice that if you have not received any news from us 1 month after the closing date you should consider