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Field
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methods to improve the deployment, adaptation capabilities and safety of robots and critical infrastructures. The developed algorithms will be evaluated on legged robots, wheel-based robots and under
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(terrestrial and NTN). The goal of this research is to design and develop algorithms and techniques that adapt to the environment, minimizing signaling overhead associated with channel estimation and enhancing
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the deployment, adaptation capabilities and safety of robots and critical infrastructures. The developed algorithms will be evaluated on legged robots, wheel-based robots and under-actuated large-scale
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Centre for Advanced Robotics Technology Innovation (CARTIN) is looking for a candidate to join them as a Research Fellow. Key Responsibilities: Develop novel algorithms for multi-agent inverse
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/ machine learning algorithms to support research in the IDMxS Analytics Cluster. The RF will apply/ improve machine learning algorithms to process (e.g., classify, predict) data collected by IDMxS. Help
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processing algorithms from concept to implementation. Eligibility to obtain a United States SECRET clearance (or higher) is required for ongoing employment in this position Minimum Qualifications: 1
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will work closely with the Principal Investigator (PI), Co-PI, and the research team to develop deep learning-based computer vision algorithms and software for object detection, classification, and
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-making algorithm for autonomous vehicles. The work will involve sensor fusion, perception, trajectory prediction and test rig set-up, and experimental validation. Job Requirements: PhD Degree in Vehicle
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This research project aims to establish the theoretical and algorithmic foundations of quantum adversarial machine learning, an emerging field at the intersection of quantum computing and machine learning. It
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-quality papers in top journals and conferences. The appointees will be required to: (a) develop novel AI and XR algorithms/software for medical image analysis and computer-assisted surgery tasks; (b