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are demonstrated knowledge related to acoustic modelling, measurement and soundscape. o Essential are demonstrated data analytic skills, ideally with machine learning or statistical modelling • Other general
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computing platforms outperforms traditional compute platforms. We invite applicants to join us as a Research Fellow or Senior Researcher (full-time). You will be part of the Continental-NTU Corporate Lab
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from the Department of Civil and Environmental Engineering. This position is part of an exciting research programme aimed at advancing the multi-robotic wire-arc directed energy deposition technology and
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that are relevant to industry demands while working on research projects in SIT. This role supports the Future Ship and System Design (FSSD) Programme, which aims to accelerate the decarbonisation and digitalisation
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quantum sensing technologies (e.g., Rydberg atomic sensors) for wireless communications and sensing. Key Responsibilities: Develop quantum-related theories, models, and algorithms for various communications
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) The Centre for Quantum Technologies (CQT) in Singapore brings together physicists, computer scientists and engineers to do basic research on quantum physics and to build devices based on quantum phenomena
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Engineering, Automation, Mechanical Engineering, Control Engineering, Mechatronics, Computer Science, AI, etc. Strong background in autonomous driving, deep learning, interaction modelling, prediction, robotics
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prediction models in Neurology using EEG data via Deep Learning (DL) techniques. In this prospective and longitudinal study, the outcome of interest is cognition over time. This position will be under
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, including machine learning, computer vision, adaptive data modelling, and computational imaging. The objective is to develop state-of-the-art machine learning algorithms for solving ill-posed inverse problems
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, including machine learning, computer vision, adaptive data modelling, and computational imaging. The objective is to develop state-of-the-art machine learning algorithms for solving ill-posed inverse problems