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Saelens team. Research Project In this research project you will develop probabilistic deep-learning models that automatically extract biological and statistical knowledge from in vivo perturbational omics
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programming, Bayesian deep learning, causal inference, reinforcement learning, graph neural networks, and geometric deep learning. In particular, you will be part of the Causality team under the supervision
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host chromatin pathways (DFG Research Unit DEEP-DV, FOR5200). The group uses experimental infection systems, an array of high-throughput sequencing methods, and single-molecule live-cell imaging
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across both surface and subsurface layers. This includes constructing robust feature extraction pipelines, attention-based fusion architectures, and deep learning models that accurately characterize cracks
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have strong programming skills in Python; You have knowledge of medical image processing, and machine learning and deep learning techniques; Written and spoken proficiency in (scientific) English is
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August 2026 are welcome to apply. A deep interest in, and basic knowledge of, key topics in language evolution, language change, language learning, human evolution, and communication. Hands-on experience
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? No Offer Description About cellumation cellumation is a Bremen-based deep-tech company and spin-off from the Bremen Institute of Production and Logistics (BIBA). We develop the celluveyor – a modular
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. Hu, X. Wei, X. Wu, J. Sun, J. Chen, Y. Huang, J. Chen, A deep learning-enhanced framework for multiphysics joint inversion, Geophysics, 88(1), K13-K26, 2023. https://doi.org/10.1190/geo2021-0589.1 [3
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application process here. About the position Technology development in geothermal energy and deep drilling has accelerated significantly in recent years, with major advances occurring in North America and
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. ... (Video unable to load from YouTube. Accept cookie and refresh page to watch video, or click here to open video) About the position Technology development in geothermal energy and deep drilling has