48 algorithm-development Fellowship research jobs at Nanyang Technological University
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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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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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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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(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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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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The Institute for Digital Molecular Analytics and Science (IDMxS) of the Nanyang Technological University, Singapore, is searching for a Research Fellow (RF) to develop artificial intelligence
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The Continental-NTU Corp Lab invites applications for the position of Research Fellow. Key Responsibilities: Lead the development of situation awareness, interaction behaviour modelling and decision
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Developing and integrating AI algorithms into the real development progress Preparing academic publications such as patent applications and research papers Contributing to quarterly and annual report writing
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advances the mathematical foundations, algorithms, and real-world applications of epistemic uncertainty in machine learning, with a strong focus on imprecise probabilities, uncertainty representation and