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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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Science (Team Director; Eiryo Kawakami) (7) Medical Science Deep Learning Team, Division of Applied Mathematical Science (Team Director; Jun Seita) (8) Prediction Science Research Team, Division of Applied
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Experience with deep learning frameworks such as PyTorch or TensorFlow Exposure to AI-enabled scientific workflows that couple simulation with data-driven modeling, including emerging approaches involving
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integrating human-in-the-loop reinforcement learning approaches. Responsible AI: Exploration of privacy-preserving AI techniques, enhancing AI safety, and addressing vulnerabilities and defenses in Large
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future. Fueled by curiosity and a deep sense of duty, they contribute invaluable insights to research and teaching, enriching our society. Are you inspired and driven by the desire to make a meaningful
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Intelligence Research Group at the Beijing Academy of Quantum Information Sciences (BAQIS), invites applications for Research Professor and Postdoctoral positions. Our group pioneers the deep integration
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studies. Strong background in AI/ML fundamentals and extensive experience with deep learning (DL) methods. Demonstrated proficiency in Python and machine learning frameworks (e.g., PyTorch, Jax, scikit
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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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, with a focus on building multimodal AI models to predict dental caries progression. The successful candidate will work on developing deep learning and computer vision models using longitudinal dental
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executed. In close collaboration with PhD researchers and project partners from TUM and ETH, you will contribute to the development of novel control and learning methods for aerial manipulators and multi