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Field
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The Manufacturing Technology Centre UK, and the University of Nottingham This project offers an exciting opportunity to undertake industrially linked research with engineering teams
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, behavioural and social science perspectives, user‑centred or participatory design methods, and quantitative analysis of farm data. The goal is to understand how digital dairy technologies can be designed and
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simulation results with experimental data. This project will integrate advanced AI techniques, including machine learning for parameter optimisation (e.g., Bayesian optimisation, reinforcement learning), AI
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The Manufacturing Technology Centre UK, and the University of Nottingham This project offers an exciting opportunity to undertake industrially linked research with engineering teams
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Fixed-term: The funds for this post are available for 12 months in the first instance. The successful candidate will be based in the Department of Computer Science and Technology and will join the
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Experience with life-history, developmental biology, or behavioural ecology experiments in small invertebrates Experience linking empirical data to modelling or theory Experience with controlled laboratory
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benefit from the extensive and broad expertise in AI and biomedical computing at the School of Biomedical Engineering & Imaging Sciences. The work will be done in close collaboration with a
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-centric demography and will work closely with the PI and wider team. The postholder will lead modelling components of the project and contribute to integrating theory with empirical data. The NERC-funded
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Engineering, Biomedical Engineering, Physics/Medical Physics, Materials Science/Engineering, Chemical Engineering, Data Science/Signal Processing, Biomedical Science, Biological/Human/Life Sciences, etc.) and
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equivalent in a subject relevant to the proposed PhD project. Due to nature of this project, the candidate should have a strong background in Engineering, especially chemical engineering or another closely