187 distributed-computing-"UNIS" Fellowship positions at Nanyang Technological University
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Young and research-intensive, Nanyang Technological University, Singapore (NTU Singapore) is ranked among the world’s top universities. NTU’s College of Computing and Data Science (CCDS) is a
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We are seeking a Research Fellow to lead research on advanced Rydberg atom–based quantum sensing platforms at CQT, NTU. The role involves experimental work on electromagnetic signature detection, developing robust sensing protocols, and delivering solutions for real-world applications. The...
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Young and research-intensive, Nanyang Technological University, Singapore (NTU Singapore) is ranked among the world’s top universities. NTU’s College of Computing and Data Science (CCDS) is a
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institutions and expertise in secure distributed systems will be highly valued, enabling the candidate to bring transferable knowledge to address the security challenges in emerging blockchain ecosystems and
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Young and research-intensive, Nanyang Technological University, Singapore (NTU Singapore) is ranked among the world’s top universities. NTU’s College of Computing and Data Science (CCDS) is a
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Young and research-intensive, Nanyang Technological University, Singapore (NTU Singapore) is ranked among the world’s top universities. NTU’s College of Computing and Data Science (CCDS) is a
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requirements: PhD degree in Computer Science, Electrical and Electronic Engineering, or related field. At least 3 years of relevant experience in computer vision, artificial intelligence, etc. Proficiency in
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Young and research-intensive, Nanyang Technological University, Singapore (NTU Singapore) is ranked among the world’s top universities. NTU’s College of Computing and Data Science (CCDS) is a
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computing. With extensive experience in medical image analysis, computer vision, and AI systems through collaborations with leading institutions. Key Responsibilities: Conduct advanced research in the areas
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Engineering, Computer Science, Applied Mathematics or equivalent. Strong background in machine learning, convex optimization, or distributed systems. Prior experience in federated learning, edge computing