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the coordination of large-scale robot systems (ground and aerial). The ideal candidate will possess hands-on experience with designing and implementing reinforcement learning algorithms, and deploying them onto real
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! Neuromorphic computing is a way to do computations with hardware that mimics the architecture of the brain. This project aims to explore and benchmark the potential of new neuromorphic hardware and algorithms
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supervised by Prof. Dr. Jun Pang. For further information or inquiries, please contact Prof. Dr. Jun Pang directly. Your profile PhD in Computer Science or a related discipline, coupled with outstanding
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of original machine-learning based algorithms and models for multi-modal ultrasound guidance that are intuitive for a non-specialist to use while scanning and trustworthy. You will work with clinical domain
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of the following: quantum field theory, quantum information, out-of-equilibrium dynamics, theoretical cosmology, particle physics, gravity, or quantum algorithms. Candidates are expected to demonstrate
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with data science, and data management (including IoT, Edge, and HPC). This is a fully funded position for 24 months within the HEXAPIC project, conducted in collaboration with Prof. Leon Kos' team
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at New York University Abu Dhabi seeks to recruit a motivated post-doctoral associate with a strong background in game theory, control systems, and/or learning theory to join the research team of Prof
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with data science, and data management (including IoT, Edge, and HPC). This is a fully funded position for 12 months within the HEXAPIC project, conducted in collaboration with Prof. Leon Kos' team
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contributing to developing and implementing novel algorithms at the intersection of computational physics and machine learning for the data-driven discovery of physical models. You will be working primarily with
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, estimation, and identification algorithms that directly interface with physical hardware. We work closely with industry partners. Our research has led to several methods now used in commercial products. We