240 software-formal-method-phd Fellowship positions at Nanyang Technological University
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We are seeking to appoint a Research Fellow to contribute to NTU’s mission of advancing cutting-edge research and industry translation in software engineering and cybersecurity. The successful
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performance checks. Monitor scans and troubleshoot basic operational issues during imaging. Reconstruct CT scan datasets using appropriate reconstruction software. Perform image processing, segmentation, and
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on matters related to the project, purchasing equipment and software, and answering queries about the project. Job Requirements: At least a PhD in information studies, information science, or related social
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. The Research Fellow is expected to be physically present at NTU during working hours. Office space, computing resources, and access to NTU facilities and licensed software will be provided. Requirements PhD in
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) who is highly skilled in and deeply passionate about computational electromagnetism and mathematical physics/engineering. The SRF should have strong background in computational methods for solving
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of faculty, students and alumni who are shaping the future of AI, Data Science and Computing. Key Responsibilities: Literature review of existing methods and models Identify the weaknesses of existing models
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for building Data+AI systems. Wring research papers of high quality based on research results Building deployable Data+AI systems based on the research results. Job Requirements: Preferably PhD in Computer
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the experimental work Develop the surface treatment methods to slow down the hydrogen intake Collaborate with internal and external stakeholders on theoretical analysis and microstructure characterization To help
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AI methods and systems, and support the University’s mission in advancing high-impact research, innovation, and global research excellence in AI and computing. Job Responsibilities: Expected to work
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of scalable machine learning systems using convex/nonconvex optimization and federated learning methods. Develop software prototypes for AI-for-Science systems tailored to scientific discovery and data