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collaborative research projects, develop novel computational algorithms, and contribute to high-quality publication and grant-related activities. The position offers opportunities to work in a dynamic research
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postdoctoral researcher with a solid background in one or more of the following areas: game theory, optimization algorithms, and numerical methods. The successful candidate will develop efficient algorithms and
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of science; (b) develop novel metrics and algorithms for AI explainability; and (c) create a tight feedback loop where (a) and (b) can iteratively refine each other. As a postdoc, you will be based in the Data
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-driven research group working at the intersection of computational genomics, clinical artificial intelligence, and imaging genetics. This position offers an exciting opportunity to develop novel algorithms
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of optimization and generalization to inform the design of practical training algorithms. To produce high-quality publications in top-tier machine learning conferences and journals. To offer guidance and assistance
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Associate to join the Parallel Systems Lab (https://psl-ntu.github.io ) at NTU’s CCDS. The role focuses on designing, developing, and evaluating efficient, scalable systems for modern multi-agent HPC-AI
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collaborative research projects, develop novel computational algorithms, and contribute to high-quality publication and grant-related activities. The position offers opportunities to work in a dynamic research
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algorithms for digital health and AI-driven research projects. Lead technical innovation by exploring and implementing emerging AI methodologies. Support data platform development and retrospective data
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algorithms for mobile robots. Implement and accelerate visual algorithms for mobile robots on embedded platforms. Develop a visual embedded platform on a mobile robot. Conduct field trials with the robotic
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the correctness, robustness and reliability of deep neural networks and AI-enabled software systems. Job Responsibilities: Develop novel methods and algorithms for the verification, testing and robustness analysis