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shifts in cell state and cell fate. Integrate spatial transcriptomics data to anchor these predictions in tissue context. Develop machine learning methods (e.g. graph neural networks, variational
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Offer Description Funding: 36 months, CIFRE (https://www.anrt.asso.fr/fr/le-dispositif-cifre-7844 ) Starting date: November / December 2025 Keywords: Physically informed machine learning, Industrial
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monitoring and health monitoring of the different machine components. To this end, multiple dedicated measurement campaigns have been performed throughout the Belgian offshore zone, resulting in a large in
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species, and the emergence of previously unseen classes. Recent advances in remote sensing and machine learning provide new opportunities to address these challenges, but most current approaches
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machine learning with the logical reasoning and semantic understanding of symbolic AI (often referred to as material and design informatics) is being developed for the accelerated discovery and development
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on topics such as leadership for academic staff, time management, handling stress, and an online learning platform with 100+ different courses; 7 weeks of birth leave (partner leave) with 100% salary; partly
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an exceptional international team with expertise in all aspects of the project. Your tasks will include: • Preparation of different EO and in-situ datasets for training a machine learning model • Development of ML
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stress, and an online learning platform with 100+ different courses; 7 weeks of birth leave (partner leave) with 100% salary; partly paid parental leave; the possibility of setting up a workplace at home
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. The candidate will also collaborate with the Department of Computer Science at Kiel University and the remote sensing company EOMAP GmbH, employing state-of-the-art machine learning techniques to improve
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. Fe, S) on CNT purity and structure. Evaluate CNTs as conductive additives in standard Li-ion battery electrodes. Apply AI/machine learning to optimise experimental design and growth parameters