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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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a 3D printing system for melting and extruding lunar regolith, while also advancing the field of composite 3D printing through experimental testing and process development. This position bridges hands
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latest predictive and generative AI for materials, we can offer you the best possible foundation. We seek two highly motivated and talented PhD students to join our group at DTU Compute, and we offer
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models and reinforcement learning models for 3D graphs of materials to explore vast inorganic chemical spaces and design synthesizable energy materials. You will couple such models with physics simulation
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infection, by exploring both 3D cultures of epithelial cells on collagen-based scaffolds, and commercially available ex vivo skin models. Focus will be on major wound pathogens S. aureus and P. aeruginosa