43 algorithm-"Prof"-"Prof" Fellowship research jobs at Nanyang Technological University
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, quantum machine learning, quantum algorithms from well-established universities/institutes. The candidates must be highly motivated in multidisciplinary research. He/she must have proven experience in
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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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/ 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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-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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a Research Fellow to contribute to a project focused on algorithm design in Game Theory and Fair Division. Key Responsibilities: Formulate mathematical models for research problems in computational
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state-of-the-art facilities to work on the following: Developing advanced path planning, search, and exploration algorithms for multi-UAVs systems in unknown and complex 3D environments. Designing
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Responsibilities: Conduct in-depth research in sublinear time and learning augmented algorithms. Design, develop, and implement novel algorithms and models. Publish research findings in leading international
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. The successful candidate will play a pivotal role in a project centered around variational quantum algorithm in the near-term, especially on innovating advanced error mitigation or detection techniques to solve
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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