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constellation of SciLifeLab researchers and infrastructure units. This position is embedded in Avlant Nilsson’s research group at Karolinska Institutet and SciLifeLab. Our lab develops deep learning models
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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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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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-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
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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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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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, and artificial intelligence methods. Assess drought stress and identify physiological traits associated with drought tolerance using advanced imaging technologies. Develop machine learning and deep
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collaborative discussions. You must hold a PhD/DPhil in Statistics, Statistical Machine Learning, Deep Generative Modelling, or a closely related field, together with relevant postdoctoral research experience