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clusters, biophysics, solids and surfaces, machine learning, quantum computing, and self-consistent fields. We develop new theory and associated computational tools, which are supported and distributed
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Transactions on Probabilistic Machine Learning. A Gelman, A Vehtari, D Simpson, CC Margossian, B Carpenter, Y Yao, L Kennedy, J Gabry, PC Bürkner, M Modrák (2020). Bayesian Workflow. B Carpenter, A Gelman, MD
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, Mendelian randomisation, and other statistical and machine-learning methods. The appointed researcher will have research interests aligned with those of our groups and the freedom to develop their own ideas
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relevant field (e.g. NLP, AI, Machine Learning) and be able to demonstrate active, collegial engagement in teaching, research, and administration, commensurate with their stage of career. The candidate will
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developing cutting-edge computer vision and deep learning aimed at optimising inspection and monitoring of infrastructure. Applying these advanced technologies to real-world infrastructure challenges through
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. The successful applicant will have the opportunity to develop skills in mathematical modelling, advanced numerical simulations and machine learning. Fully involved in the basic research in these areas whilst also
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/ ). Your tasks will include data collection, analysis, write-up, and dissemination of ongoing and future research. Furthermore, you will play a crucial role in supporting and training PhD students and other
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/ statistics, an excellent research record and an interest in biological / clinical applications of statistical and ML approaches. Postdoctoral experience in machine learning, statistics is desirable. Experience
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protein design and evolution, using molecular biology and biophysics along with the latest AI or machine learning tools. According to the development of the project there may be the chance to learn other
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, manipulate large datasets, visualise data and perform numerical and statistical analysis is a requirement. Experience in handling 'big data', machine learning and working in distributed teams, is useful