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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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Agency funded BILMo (Biodiversity Inspired Lake Modelling) project, which aims to upgrade different mechanistic lake models to 1) predict diversity and community composition responses to combined gradients
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and component reliability. You are encouraged to visit the ESA website: https://www.esa.int/ Field(s) of activity/research for the traineeship Growing mission complexity, the need for European
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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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antigens presented by MHC molecules. This curiosity-driven project develops cutting-edge AI technology for 3D TCR–pMHC modeling to improve neoantigen identification, TCR specificity prediction, and TCR
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provide meaningful explanations of their predictions to downstream users. A central aim of this project is to investigate how Vision-Language Models (VLMs), Multimodal Large Language Models (MLLMs), and
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mathematical foundations needed to make deep operators reliable, robust, and applicable for control of complex engineering systems. In this PhD project, you will investigate how operator-learning models can
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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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-wide traffic prediction Design physically consistent and interpretable machine-learning methods for dynamic traffic systems Test and validate prediction models using large-scale real-world traffic data
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of multimodal prediction models to detect and predict atrial fibrillation (AF) and other clinically relevant cardiac rhythm patterns, predict disease progression and treatment response, and support personalised