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Post-harvest pathology Biomarkers, volatiles, and sensors Cold chains and refrigeration technology Data analysis and modelling (R, Python, CFD) Besides that, you have demonstrable experience in project
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to science, engineering and society. You will focus on optimization-based, data-driven and partially model-based control methods. You will have access to a strong research network and a broad range of
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electronic solutions for future AI-driven optical interconnects. Design, implement and characterize the most promising topology for driver and TIA in advanced semiconductor technology
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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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driven by curiosity and has: A Master’s degree in Mechanical Engineering, Aerospace Engineering or equivalent. Good team-working abilities and a positive can-do mentality. Strong reporting and
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. The project will bridge wind farm aerodynamics, advanced control, system identification, filtering, and data-driven modelling, with a strong emphasis on combining physical knowledge with measurements rather
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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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knowledge, innovations, and solutions that help move the world forward. Faculty Mechanical Engineering From chip to ship. From machine to human being. From idea to solution. Driven by a deep-rooted desire to
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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