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Kontogianni. Our research explores how intelligent systems can perceive, understand, and interact with the 3D world. We develop new methods in computer vision, machine learning, and multimodal 3D
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engineered 3D hydrogels, we will experimentally probe the mechanical forces and physical constraints that drive coordinated cell behavior. In parallel, we will develop and apply computational models and
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detailed data about forest ecosystems. To convert the captured data into meaningful information about the forest environment we seek a PhD candidate who wishes to advance state-of-the-art computer vision
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computer vision models for forest-based 3D point cloud data. In recent years, large advances have been made for deep learning algorithms for high-resolution point clouds from small geographic areas. We seek
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, to fabricate computed active materials and smart structures. These advanced AM techniques offer valuable and diverse material deposition capabilities for creating 2D-to-3D shapes and shapeshifting lattice
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Max Planck Institute for Intelligent Systems, Tübingen site, Tübingen | Bingen am Rhein, Rheinland Pfalz | Germany | 8 days ago
, virtual reality, biology and medicine. Using unique 3D & 4D capture facilities, machine learning, computer vision and advanced graphics, we are modeling humans and animals shape and behavior. In the Eye
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Computer vision (3D, detection, classification, segmentation, object tracking). Autonomy, creativity, and interest in real-world AI applications. Interest in agriculture or agri-food. What We Offer
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research group in computer vision and machine learning, with seminal results in 3D reconstruction from images, scene understanding, deep learning, optimization, sparsity, etc. IMAGINE is part of
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the organization of DNA and its relation to the dynamic 3D-structured chromosomes. The student will form a part of our new NEST initiative funded by the Wallenberg AI, Autonomous Systems and Software Program (WASP
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organization. We invite applications from motivated candidates with passion and a strong interest in conducting research and innovation activities on crop modeling, remote sensing, and computer vision to predict