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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
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work with our team to conduct research on the development of image analysis algorithms and AI methods for hardware security evaluation. The roles of this position include: Study literatures on multi
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Processing and Machine Learning to develop signal processing and machine learning algorithms and methods for drone swarms. The role will focus on visual localization techniques. Key Responsibilities: Develop
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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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of performance, speed, and precision. Key Responsibilities: Design and implement genAI models for embodied AI systems. Develop and optimize deep learning algorithms to enable robotic arms to perform complex tasks
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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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studies for project-based research topics. Contribute to the development of algorithms and models to enhance the reasoning abilities of large language models in the healthcare domain. Job Requirements
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operation. Develop modular architectures for multi-agent coordination, sensing, and communication. Integrate sensor suites, flight controllers, and swarm coordination algorithms into UAV platforms. Conduct
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The Continental-NTU Corp Lab is a strategic research collaboration between NTU and Continental, focusing on developing technically advanced solutions in the areas such as sustainable materials