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multidisciplinary team driving transformative sensing technologies. Key Responsibilities: Develop and optimize fabrication processes for sensor arrays based on 2D materials (e.g., graphene, MoS₂), including flexible
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communication skills and knowledge of common computer applications, e.g. MS office; Remuneration will be commensurate with the candidate’s qualifications and experience. Informal enquiries are welcome and should
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devices, smartphones, questionnaires and computer-based behavioral tests to collect large-scale, multi-sensor data streams. The research assistant will join a dynamic and multidisciplinary team conducting
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to ensure all project deliverables are met. • Design a Natural Language Processing algorithm for identifying Personal Identity Information data. • Design and evaluate privacy preserved Generative AI-based
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in image processing, quantitative analysis, and biological interpretation Proficiency in AI/machine learning tools for image segmentation, transformation, registration, or tracking Solid mathematical
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for Quantum Technologies (CQT) 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
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to uncover SRL patterns in video-based learning (VBL) and digital game-based learning (DGBL) environments; • Conduct process mining and network analysis to differentiate SRL patterns between high- and low
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of nutrients and macromolecules To automate the process of complex fabrication of foods To develop printing instruments intended for use in specific scenarios The researcher will work in an interdisciplinary
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for motion control, and monitoring sensors. Job Requirements BS in Electrical and Electronic Engineering, Mechanical Engineering, computer engineering, or related field 4-year research experience in related
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, electrical & electronic engineering, or equivalent. Background knowledge in signal representation/processing, visual data compression, and data-driven and machine learning/analysis. Prior research experience