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, multimodal foundation models, continuous learning systems, or agentic AI models. Experience with state-of-the-art multimodal foundation models and agentic AI frameworks Experience in large-scale deep learning
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(PyTorch, scientific Python) with solid experience in scientific computing and software development; familiarity with C++ and Linux environments is an advantage Strong background in deep learning for image
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include the development of finite elements methods, as well as inverse design strategies based on deep-learning and Neural Networks approaches. The latter will then bring the project to the experimental
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, Python, Bash). Good level on machine learning. Good level of written and oral English. Ease in a multidisciplinary environment, taste for teamwork, interpersonal skills. Scientific curiosity
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the following areas: deep learning, reinforcement learning, imitation learning, robot perception, navigation, and manipulation. Experience with whole-body control, humanoid or multi-DOF platforms, and
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and polymers. The Wentz Lab is a collaborative, multidisciplinary laboratory environment, and the successful applicant will play a vital role within our emerging research team. The hired postdoc fellow
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(postdoc) Limited until: 30.04.2029 Reference no.: 5322 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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of almost 11,000 individuals, including approximately 7,700 academic staff members, who passionately pursue answers to the profound questions that shape our future. Fueled by curiosity and a deep sense
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). The ideal candidate brings a strong machine learning foundation, curiosity about sound and music computing, and enthusiasm for collaborating with PhD students and postdocs. You will help combine individual
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comparing supervised and unsupervised methods (e.g., regularized regression, tree-based models, ensemble methods, clustering, dimensionality reduction) and deep learning approaches Developing and applying