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of GPUs and/or time in either training or inference procedures, which pose considerable challenges to both academia and industry for widespread access and deployment. In particular, the sampling process of
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addressing specific case studies or specific targeted techniques. The main tools to be used will come from the discipline of Machine Learning, particularly those based on Bayesian methods. The student will be
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Vacancies Two PhD positions on Flexible and User-adaptive statistical inference Key takeaways You will develop a mathematical framework for multiple testing, enabling flexibility in study design
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, compression, learning, and inference for classical and quantum data exchanged through classical and quantum networks. The objective of the PhD study is to explore and address research and design challenges
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will be grounded in rigorous mathematics coupled with a sound understanding of the underlying earthworm ecology. Bayesian inference methodologies will be developed to estimate where and when behavioural
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; Midlands Graduate School Doctoral Training Partnership | Nottingham, England | United Kingdom | about 2 months ago
ESRC DTP Strategic Joint Studentship University of Nottingham and University of Birmingham The Midlands Graduate School is an accredited Economic and Social Research Council (ESRC) Doctoral Training Partnership (DTP). One of 15 such partnerships in the UK, the Midlands Graduate School is a...
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analyses, an area in which our group has a track record of success (see recent publications below). The TARGET-AI project seeks to apply leading-edge techniques from deep learning and Bayesian modeling
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techniques that are useful for the modelling of many real-life systems. These include the development and analysis of stochastic models, computer simulations, differential equations, statistical inference
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; mathematical modelling of cancer; probabilistic modelling and Bayesian inference, stochastic algorithms and simulation-based inference; causal inference and time-to-event analysis; and statistical machine
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behaviour using computational approaches such as Bayesian program synthesis and inverse reinforcement learning. Investigate the diversity of motor commands that could implement observed behaviours and explore