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Field
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Human-Computer Interaction, Information Science, Computer Science, Design, or related fields - Strong record of published research in HCI, CSCW, DIS, or related venues - Demonstrated ability in
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. Qualifications • PhD Degree in a relevant discipline, e.g. electrical / electronic engineering, computer engineering, computer science, etc. • Full experience in computer graphics and robotics area
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confidence set (credibility set if prediction is Bayesian) for a multivariate estimate with statistical coverage guarantees. This PhD project aims to develop new CP methods for knowledge graphs (KGs), which
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(IRT) models in small samples. The ideal candidate has prior knowledge of IRT models, a basic understanding of common estimation methods, and strong programming skills in R, Python, or another relevant
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aspects of health at NUS and in Singapore, and beyond; and to develop interdisciplinary translational research and evaluation methods to support our evidence-based approach. We aspire to become the leading
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research using methods such as sensing technique, 3D printing, human-computer interaction, simulation, and/or machine learning to address challenges in machinery motion planning and construction safety
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skills relevant to maintenance, repair, and modification of scientific instruments. Qualifications Experience with biological experimental design and implementation. Computer skills for instrument
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electrical engineering, computer science, computer engineering, social science or any other related fields. A strong track record of high-quality research in formal method based robotic operational
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computer simulations Test the methods via lab experiments Publish results in top-tier journals in related fields Assist in mentoring PhD students Job Requirements: A PhD degree in control systems engineering
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publication of research or research communication. Use of computer programming as a method of research and inquiry. Applicants will be evaluated according to admission requirements in The Faculty of Humanities