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qualifications Publications at top machine learning or computer vision conferences (NeurIPS, ICML, ICLR, CVPR, AISTATS etc.) are highly meriting. Expertise in Bayesian methods, generative models, multimodal models
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analyses. The postdoc will be hosted at TDB, co-supervised by both groups, and will work at the interface of scientific computing, machine learning and particle physics. Project description Searches for dark
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and variation. The successful candidate will develop innovative methods and models to advance our understanding of genome evolution and variation. The position is based in the Computational Genomics
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