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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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One Research Associate position exists in the data-driven mechanics Laboratory at the Department of Engineering. The role is to set up a machine learning framework to predict the plastic behaviour
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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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) in PhD/postdoc/job; has a good publishing track record, and has the ability to work in a team and with collaborators. The experience of system and component level testing in optical systems is an
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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
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language processing (NLP), large language models (LLMs), machine learning (ML), and data visualization. The candidate will leverage their expertise in AI, statistics, and programming to design, develop, and evaluate
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) in a relevant subject (Physics, Chemistry, Materials Science, Chemical Engineering), experimental track record and willingness to learn. Home rate fees are fully funded. Applicants from overseas will