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Can you help unlock the data needed for the energy transition? In the NWO-funded SHARE project, you will develop AI models that generate realistic, privacy-preserving synthetic energy data for grid
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phenotyping, microbiome profiling, predictive modelling and targeted experimental validation to identify the microbial factors that make plants more resilient to disease. Your job You will join the Plant
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19 Sep 2026 Job Information Organisation/Company Radboud University Research Field Computer science » Modelling tools Computer science » Programming Engineering » Computer engineering Engineering
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candidates, 7 postdoctoral researchers and 1 PDEng, allowing close collaboration across disciplines including plant physiology, crop modelling, greenhouse technology and systems engineering. As a PhD candidate
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Are you interested in developing next-generation modelling tools for sustainable food production? Do you enjoy working at the interface of engineering, environmental sciences, and systems analysis
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measurements and process-based modelling to identify the mechanisms linking vegetation, soil microorganisms and ecosystem carbon cycling. The project spans laboratory, field and ecosystem scales and combines
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help unlock the data needed for the energy transition? In the NWO-funded SHARE project, you will develop AI models that generate realistic, privacy-preserving synthetic energy data for grid planning and
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plant phenotyping, microbiome profiling, predictive modelling and targeted experimental validation to identify the microbial factors that make plants more resilient to disease. Your job You will join the
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; developing innovative data models in collaboration with a postdoctoral researcher and other consortium partners; identifying biomarker candidates for next-generation miniaturized screening assays; presenting
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to develop engineering interventions to improve plant regeneration, seed longevity and defenses against disease. Your task will be to further develop two-dimensional and three-dimensional models of plant