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or physiology. Further, postdocs should have a deep interest in scientific collaboration between researchers using theoretical and empirical approaches. The five projects are: A. Sensing the breaking point
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infrastructure, mobility demand, and power grid operations. On top of this environment, a deep-learning-based learning will be developed to enable decentralized and coordinated decisions on EV user charging
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heterogeneity in cancer, inflammation, and tissue senescence. • Developing next-generation deep-learning and statistical deconvolution methods for inferring gene regulation from bulk, single-cell, and spatial
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, deep learning, fNIRS, eyetracking). The postdoc will primarily be mentored by Meg Cychosz (Linguistics), but will have ample opportunity and flexibility to establish collaborations with other groups and
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measurements. Have a background in computational biology, bioinformatics, or machine learning for biological problems. Have experience with modern deep learning frameworks (PyTorch, JAX, or equivalent). Have
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, or a related field. Solid research background and practical experience in one or more of the following areas: Reinforcement Learning / Deep Reinforcement Learning Fine-tuning and Application of Large
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. B1 lit. b (postdoc) Limited until: 31.08.2032 Reference no.: 5718 Explore and teach at the University of Vienna, where over 7,500 brilliant minds have found a unique balance of freedom and support
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analysis packages, basic shell scripting, experience in Unix/Linux platform) and experiences with deep learning tools (e.g., PyTorch, TensorFLow, Keras), neuroimaging analysis tools (e.g., PMOD, SPM, FSL
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: §48 VwGr. B1 lit. b (postdoc) Reference no.: 5892 Explore and teach at the University of Vienna, where over 7,500 brilliant minds have found a unique balance of freedom and support. Join us if you’re
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subjects and research areas; Experience with one or more general purpose programming languages, for example Python, and general purpose deep learning frameworks, such as Tensorflow or PyTorch; An interest in