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-varying photogrammetry 3D point clouds of growing plants for high throughput phenotyping applications. A key part of the project is to craft training data for a Deep Learning-based method aimed
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, applied mathematics, neuroscience, or a related field. Proven experience in machine learning, deep learning, generative AI and data mining. Strong programming skills (e.g., Python, R, MATLAB, or similar
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. Strongly Preferred Qualifications: Expertise in weather forecasting or climate modeling/dynamics; Familiarity with theoretical and practical aspects of scientific deep learning; Experience working with
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learning libraries (e.g., PyTorch) Desirable criteria Research experience in one or more of the following areas: tactile sensing, robot grasping and manipulation, robot control, computer vision, deep
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research profile, and an international network around big data in marine sciences. The candidate will have access to NIOZ’s high-performance computing cluster, GPU nodes for deep learning, dedicated data
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artificial intelligence—especially deep learning—offers transformative potential for developing next-generation earth system models. Recent breakthroughs, such as neural network-based short-to-medium term
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adaptation; reinforcement learning and inverse reinforcement learning. o Machine Learning & Intelligence, including machine learning and adaptation; deep learning; computer vision; machine intelligence
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cardiometabolic disease. This two-year position (with the wish and possibility of extension for another four years) is ideal for a scientist with deep technical expertise and passion of alleviating disease burden
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. Panagiotis Papadakis and Associate Prof. Mihai Andries Keywords: Deep learning, event cameras, human skeleton, pose estimation, action recognition Where to apply Website https://imtatlantique.fillout.com
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, deep learning and AI technologies while anticipating faculty needs and strategically advocating for growth in Princeton-offered services. Responsible for understanding changes to campus need and