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Field
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: to develop next-generation autonomous crop monitoring and decision-support systems for Controlled Environment Agriculture. By integrating plant sensing, data and crop models, we aim to enable more precise and
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industry. Our group combines precision experiments, advanced imaging, and modeling to uncover the physics of tin droplets under extreme conditions of laser irradiation. We have established a strong track
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: PhD in Chemical Engineering or related field Required Education: 1 year of prior research experience on multiscale modeling, hybrid modeling, and model-based control or related fields Desired Experience
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, and traceability in accordance with the GDPR and the EU AI Act. Integrate predictive virtual biopsy models in distributed environments. Lead pilot experiments and monitor the convergence of federated
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. Desirable experience in AI-assisted image analysis, machine learning, computational modelling, or building predictive models from biological imaging or cell–material interaction datasets. Strong experience in
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emulation, active-comparator new-user designs, self-controlled case series and case-crossover studies, where appropriate. The role will also involve developing and validating clinical risk prediction models
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candidate with a PhD degree in computer science, physical chemistry, chemical physics, theoretical physics, or a related field, with a strong background in training GNN-based ML predictive models (Equiformer
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will also be integrated into the wider CENSEMAT research environment at Aarhus University, allowing computed models and predictions to be tested directly against advanced experimental characterisation
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planetary atmospheres. The Section also initiates and manages a wide range of related modelling, software and hardware R&D activities. You are encouraged to visit the ESA website: https://www.esa.int/ Field(s
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validation, while establishing protocols for sensor calibration, spatial sampling, quality control and integration with Earth Observation data. Develop spatial, statistical and predictive models to investigate