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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
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quality and evidence grounding Calibration, uncertainty, and appropriate deferral Trace auditability and clinician-in-the-loop evaluation Profile Must Have PhD in Computer Science, Machine Learning, Medical
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growth of deep tech and industrial startups. A cross-cutting objective is to establish scalable data infrastructures and methodologies that enable broader use of public registry data among ESSEC faculty
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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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AWI - Alfred Wegener Institute Helmholtz Centre for Polar and Marine Research | Bremerhaven, Bremen | Germany | about 2 months ago
of convection in the vertical exchange of climate-relevant tracers such as carbon and heat between the surface and deep ocean in the seasonally sea-ice covered Southern Ocean. Your Tasks You will contribute
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populations. Apply Artificial Intelligence (AI) methods including deep learning (DL) models and supervised and unsupervised machine learning (ML) methods for integration and for Genome-2-Phenome (G2P) and risk
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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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leverage reinforcement learning, deep learning, and generative AI, and evaluate against the research front in mathematical optimization strategies, to enable efficient, robust, and adaptive evacuation
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populations. Apply Artificial Intelligence (AI) methods including deep learning (DL) models and supervised and unsupervised machine learning (ML) methods for integration and for Genome-2-Phenome (G2P) and risk
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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