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on novel agent architectures, including tool-use methodologies, advanced planning algorithms, and multi-agent collaboration for simulation-based optimization. Innovate & Conceptualize: Design and
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Responsibilities: Conduct individual research within the designed project: process data, develop research methods, build and evaluate computer vision and machine learning algorithms empirically. Author research
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purposes to meet multiple information and strategic requirements for the various stakeholders of the university. The successful candidate will join a team of other data analysts and data scientists to engage
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, including machine learning, computer vision, adaptive data modelling, and computational imaging. The objective is to develop state-of-the-art machine learning algorithms for solving ill-posed inverse problems
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validate advanced 5G features such as network slicing, MEC and xApp/rApp. Contribute to the development of innovative solutions and algorithms to enhance 5G network capabilities. Work closely with
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validate advanced 5G features such as network slicing, MEC and xApp/rApp. Contribute to the development of innovative solutions and algorithms to enhance 5G network capabilities. Work closely with
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) Design robust obstacle avoidance algorithms for mobile robots in dynamically changing environments, focusing on formal safety constraints and real-time performance in unpredictable conditions. b) Develop
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to pioneering research in the field of robotics. Key Responsibilities: Design, implement, and test robust software for robot localization, mapping, and navigation. Develop and refine algorithms for sensor fusion
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, including machine learning, computer vision, adaptive data modelling, and computational imaging. The objective is to develop state-of-the-art machine learning algorithms for solving ill-posed inverse problems
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on AI-driven end-to-end autonomous driving algorithms. Key Responsibilities: The research fellow will be leading the development of AI-driven end-to-end autonomous driving algorithms. The work will