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security-related projects. Disseminate research findings through conferences, invited talks, and outreach activities, strengthening NTU’s leadership in infrastructure security R&D. Job Requirements: PhD in
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Requirements: PhD degree in physics, engineering or related field. Familiarity with electrodynamics and electromagnetism. Good written and oral communication skills. Proficiency in scientific programming e.g., C
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Qualifications: A Masters or PhD in Psychology/Behavioral Science/Developmental Psychology/Education/Public Health or any discipline related to child development. Experience: Candidates with the following skills
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. (https://cde.nus.edu.sg/mse/staff/ming-zhao/;https://www.mingzhaogroup.com/) Qualifications PhD degree in materials, chemistry, chemical engineering, physics, environmental engineering, or any other
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Associate) PhD in smart grids, energy management, or mathematical optimizations (for Research Fellow). The candidates who have submitted the thesis are also encouraged to apply. Background in the application
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Requirements: MSc (Research Associate) or PhD (Research Fellow) in Mathematics or Computer Science or closely related fields. Ability to design and implement advanced algorithms and data structures. Independent
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the fellow in training, setup, and execution of the project. Qualifications Candidates with a PhD in engineering, biology, biomedical sciences, or related fields are encouraged to apply. A strong background in
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to the scientific community Job Requirements: PhD in chemistry, physics, material science, computer science or an allied field Experience with quantum computing frameworks, specifically Pennylane and Qiskit
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Requirements: PhD degree in physics Demonstrated experience in computer sciences Demonstrated experience in handling large size database Knowledgeable in theoretical physics, and at minima basic knowledge in
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: PhD in Materials Science, Chemistry, Physics, Computer Science, or a related field. Strong expertise in machine learning for materials science (e.g., generative models, neural networks, active learning