14 distributed-algorithm-"UNIS" Fellowship positions at National University of Singapore
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Job Description Job Alerts Link Apply now Job Title: Visiting Research Fellow for Quantum Algorithms Posting Start Date: 19/06/2025 Job Description: About the Centre for Quantum Technologies (CQT
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Job Description Job Alerts Link Apply now Job Title: Research Fellow (Time Synchronization of Distributed Radar Sensors) Posting Start Date: 02/05/2025 Job Description: Job Description For a project
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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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Power Engineering • Relevant experience in power electronics, wide band gap semiconductor devices, multilevel inverters, soft-switching high-frequency power converters, drives, control algorithms
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the COVID-19 vaccines) is a highly dynamic and fast moving field. We have developed a generative AI algorithm to optimize the mRNA, and we are looking for an experienced wetlab researcher to test the
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with major in Power Engineering • Relevant experience in power electronics, drives, control algorithms, optimization techniques, and optimal energy management algorithm development for the optimal
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Analytics & Explainability development of algorithm and system for the project The School of Computing at the National University of Singapore (NUS) invites applications for a Postdoctoral Research Fellow
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Roles Lead a retrospective study utilizing a decade of health data to create a comprehensive HRI database. Investigate the distribution and determinants of HRI by applying epidemiological methods
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ethical and security standards. Concept and Algorithm Development: Innovate in data science, machine learning, and AI. Data Analysis and Reporting: Contribute to data analysis, reporting, and publication
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develop algorithms to identify and predict SRL subprocesses from multimodal learning data (e.g., EEG/fNIRS, eye-tracking, and think-aloud protocols); • Analyze large-scale learning analytics data