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(GenIR), a new and rapidly evolving retrieval paradigm where generative models are used to directly generate document identifiers given a user query. This paradigm departs from traditional multi-stage
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applications involving image analysis, real-time monitoring, or complex process optimization. You have hands-on experience with model optimization techniques such as post-training quantization (PTQ
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generate document identifiers given a user query. This paradigm departs from traditional multi-stage retrieval pipelines and instead integrates the indexing and retrieval process into a single, end-to-end
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elaborate the prototype of the audit tool. Your duties and responsibilities include: The co-development and testing of the audit tool Social and economic analysis of the implementation of the Audit tool Your
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in Data Science, Artificial Intelligence, Computer Science, Cognitive Science, or any another relevant discipline. Have interest and experience with deep learning and image analysis. Have interest and
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and document analysis. Explore what data are available on essential health resources and supporting systems, and assess their usefulness. Co-create a regional risk picture by facilitating workshops
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Observation Programmes and in particular with the Copernicus Hyperspectral Imaging Mission for the Environment (CHIME) project and Mission Science team. You will be part of the ESA Φ-lab. Our mission is to
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Postdoc in Extracellular Vesicles as Mediators of Gut-Microbiome Interactions in Parkinson's Disease
to ileostomy samples, Parkinson’s disease cohorts, and novel hydrogel/motility models. This approach allows us to reveal microbial processes that are difficult to capture with standard models, connecting patient
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assess their usefulness. Co-create a regional risk picture by facilitating workshops to prioritise event–disruption–risk combinations with compounding impacts on care (e.g., precipitation extremes
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. [4] Sivakumar et al., Phys. Rev. B 111, 075409 (2025), Influence of surface relaxations on scanning probe microscopy images of the charge density wave material 2H-NbSe2. [5] B. Kiraly et al., Nano Lett