186 Education-"https:"-"https:"-"https:"-"https:"-"U.S" Fellowship positions at National University of Singapore
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The Centre for Holistic Inquiry into Lifelong Learning (CHILL) invites applications for the position of Research Fellow in AI and Educational Technology. Working under the supervision of A/Prof
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• PhD degree in Science or Engineering • Education or a track record in applied mathematics, with a strong interest in physical sciences • A solid foundation in thermodynamics & statistical
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. The successful candidate will develop high-performance photonic devices based on lithium niobate, silicon photonics, and heterogeneous material platforms, with emphasis on electro-optic modulators, low-loss
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the supervision of the Principal Investigator, including but not limited to the following: Develop new computational tools through the application of AI / deep learning / machine learning / statistics on spatial
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closely with the Principal Investigator and research team and will have opportunities to collaborate with leading academic or industrial partners. Key Responsibilities • Develop and conduct
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the research component of the project. Write and review research papers, present research outcomes, conceptualise new ideas and develop plans for independent research which could have a considerable influence
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the Asia Pacific region as a Centre of excellence in Family Medicine and Primary Care service delivery, education and training and research. Appointments will be made on a 1-year contract basis in
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stakeholders to translate research into practical tools and workflows. Responsibilities: Develop new concepts and algorithms in data science, machine learning, and artificial intelligence for urban intelligence
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; economic statecraft; climate, fisheries, and non traditional security). Produce high quality outputs: at least 1 SSCI/Scopus journal articles per year and 1 policy briefs/working papers. Develop and maintain
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, and AI-driven computational biology. The successful candidate will develop and apply innovative computational methods to analyse large-scale multi-omic datasets, identify mutational patterns across