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doctoral programme in Technology within three months of starting in the position. (https://www.usn.no/english/research/postgraduate-studies-phd/our-phd-programmes/technology/). The doctoral programme
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Computational Imaging for High-Throughput Applications (1.0 fte) As a PhD student, you will be embedded in the research group Computational Imaging and Deep Learning (CIDL), part of the Leiden Institute
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PhD in Computational Imaging for High-Throughput Applications (1.0 fte) As a PhD student, you will be embedded in the research group Computational Imaging and Deep Learning (CIDL), part of
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, mixed-effects modeling, Bayesian methods, deep learning, variational autoencoders, generative AI). Is an experienced programmer in R and/or Python, and used to working with large datasets and reproducible
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software or similar languages and experience with modern machine learning and deep learning frameworks parallel computing using clusters like UPPMAX and GPUs for high-performance computing and parallel
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Helmholtz Zentrum München - Deutsches Forschungszentrum für Gesundheit und Umwelt | Germany | 3 months ago
immunology with deep focus on T cells and Treg biology Hands-on experience with in vivo mouse models (FELASA certification is a strong plus) Practical experience in flow cytometry (FACS), including protocol
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Are you interested in developing mathematically grounded methods for uncertainty quantification in deep learning, particularly for large language models in healthcare applications? Are you looking
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Are you interested in exploring how multi-agent aerial manipulation can contribute to construction and working at the intersection of robotics and machine learning? Job description Advancements in
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About us VIB.AI, the VIB Center for AI & Computational Biology, is a research center dedicated to integrating machine learning with deep biological insight to understand complex biological systems
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etc; Candidates with multidisciplinary backgrounds are welcome. · Strong skills in computational and data analytical methodology development and implementation; experience in machine learning and deep