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strong background in shape modelling, deep generative modelling (diffusion/transformers), or multimodal representation learning. You have strong programming skills, especially in Python, and preferably
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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
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Python and common deep learning frameworks (PyTorch) • Excellent communication skills in English (German is a plus) • Independent, structured working style and experience in supervising students Preferred
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Join us at the forefront of life science AI. We are looking for a postdoctoral researcher to develop cutting‑edge, multimodal transformer‑based deep learning methods to extract insight from genomic
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-of-the-art methods, datasets, and challenges Proven experience with: Video data processing for learning and inference Deep learning architectures for video analysis Python programming and PyTorch framework
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), Kinetic Modeling. Machine Learning Interatomic Potential (MLIP) accelerated simulations. Demonstrated ability of coding in Fortran, Shell, or Python with development experiences. Deep knowledge in excited
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deep learning including data collection, architecture development, model training, and validation Interest in software development, with particular emphasis on the Python programming language and
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of AI and Data Science : Machine and deep learning, NLP, BDI (Belief-desire-intention) systems, and Large Language Models (LLMs). Expertise in design and very good programming skills (Python, Pytorch
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23.02.2026 Application deadline : 30.04.2026 The Autonomous Systems Lab at the University of Tübingen is searching for a Postdoctoral Researcher in machine learning (m/f/d, E13 TV-L, 100%) limited
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fellowships and NSF SBE postdoctoral awards. We especially welcome applicants with theoretical interest in child language development, strong computational and analytical skills (deep learning frameworks), and