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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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for AI and deep learning (details: NVIDIA DGX-2) Intel-based Aurora Supercomputer: A next-generation supercomputing system (details: Aurora Supercomputer) Additional advanced compute architectures designed
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Adipose Tissue Childhood cohort (n~700), with deep phenotyping allowing for combining clinical, epidemiological, lifestyle and functional omics and multi-omics data. We are currently seeking a Postdoctoral
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learning and deep learning models for trait prediction and climate-resilient wheat breeding. Analyze time-series UAV data using crop models in combination with genomic and agronomic information. Collaborate
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, Pandas, SciPy, scikit-learn, PyTorch, TensorFlow) Experience developing and deploying machine learning or deep learning models Ability to present complex results to multidisciplinary teams, including
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Helmholtz Association of German Research Centres | Oldenburg Oldenburg, Niedersachsen | Germany | 3 months ago
discuss modelling methods and assumptions without requiring full understanding the mathematical intricacies of the models. Your TasksThe work will involve a deep, critical questioning of practices in
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Qualifications: A Master's degree and a PhD in Data Science, Mathematics, Computer Science, Physics, or in a related field In-depth knowledge in current methodology of AI (Deep Learning, generative AI, Explainable
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Master's degree and a PhD in Data Science, Mathematics, Computer Science, Physics, or in a related field In-depth knowledge in current methodology of AI (Deep Learning, generative AI, Explainable AI, …) and
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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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applications for a fully funded postdoctoral associate position. This position, available immediately, focuses on developing machine learning and deep learning methods for analyzing large-scale single-cell DNA