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well as interact with other members of the algorithms research group. We are looking for excellent candidates with a background and experience in one or more of the following areas: graph algorithms, parameterized
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-based networks graph-based approaches Bayesian learning information theory Documented strong programming skills (preferably Python), for example with contributions to open-source projects, with an active
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-weight spatio-temporal graphs for segmentation and ejection fraction prediction in cardiac ultrasound, MICCAI, 2023 [3]Trosten et al., Hubs and Hyperspheres: Reducing Hubness and Improving Transductive Few
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topics such as: neural networks self-supervised learning convolutional neural networks transformer-based networks graph-based approaches Bayesian learning information theory Documented strong programming