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inference to machine learning and artificial intelligence. Leiden Observatory aims to remain at the forefront of these developments — in both research and education — by strengthening its expertise in
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. The position is embedded in the context of the RVO project “SLDbatt”, in collaboration with Dutch research organisations and ESS industry partners. The SLDbatt project aims to develop and deploy battery
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; Develop system architecture and training strategy to enable the FM to learn from heterogeneous MRI data in terms of data source purpose and physical location in the scanner; Develop efficient techniques
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responsibilities include: Development of a flood classification framework for flood type prediction Comparison of different ML algorithms in a sensitivity study Communication with stakeholders Development of open
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or incomplete. Information Your tasks will include: Developing and benchmarking ML/AI algorithms tailored to low-data regimes — e.g. few-shot learning, transfer learning or data-efficient representation learning
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Location EGNOS Project Office, Toulouse, France. Our team and mission The GNSS Regional Augmentation System Division is responsible for the development of the EGNOS system and its qualification, in
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multidisciplinary project at the intersection of Robotics and wildlife conservation. The project aims to develop autonomous drones capable of perching on natural structures, inspired by the way birds rest on branches
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from multispectral datasets You will contribute to the ongoing development of Machine Learning algorithms for recognition of planetary materials from multispectral datasets. This project combines deep