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capabilities interact with operational conditions, human intervention and the wider maritime and port logistics systems. The postdoctoral researcher will develop data-driven and model-based approaches to support
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team working in the interdisciplinary field of plasma-driven nitrogen fixation. This EPSRC-funded project aims to develop a prototype plasma system for the sustainable generation of fertiliser from air
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or neural networks) on CFD data to develop a fast, data-driven wind field predictor. You will combine this surrogate model with AeoLiS and evaluate the accuracy of the new model setup by applying it to
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at least one of the following areas: crop modelling, plant sensing or data-driven crop management. Demonstrable experience in translating research insights into practical applications and collaborating with
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battery-related hydrometallurgical leaching as a model system, the project combines controlled experiments, real-time monitoring, chemical analysis, and data-driven modelling. The postdoctoral researcher
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through data-driven modeling and optimization. The successful candidate will work at the intersection of thermal-fluid sciences, control theory, and artificial intelligence/machine learning to advance
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of new treatments including in vitro and in vivo proof-of-concept efficacy data. This is an opportunity to work across multiple disciplines spanning retinal biology, viral vector technology and
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data to learn contextual representations of microbes and communities and translate them into predictive models for successful crop microbiome engineering. Your job Plant-associated microbiomes can
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engineering; energy systems; computational science; or a closely related discipline. Essential skills The candidates should have strong experience in several of the following areas: electrochemical modelling
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of both biology and (agent-driven) software engineering Fluency in written and spoken English Embraces complexity Our offer An interdisciplinary environment spanning wet-lab, technology-development and