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, feeding behavior monitoring, and associated visual analytics. Investigate and integrate physiological and behavioral data from diverse IoT environmental sensors for multi-modal stress detection together
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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
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on AI-driven end-to-end autonomous driving algorithms. Key Responsibilities: The research fellow will be leading the development of AI-driven end-to-end autonomous driving algorithms. The work will
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Responsibilities: The successful applicant will be responsible for: Obtaining theoretical results at the interface of geometry and biophysics Designing, implementing, and testing algorithms to model active matter
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ICs. Development cycle including circuit design, simulation, modeling, layout, verification and measurements Design high power-efficiency RF power amplifiers Develop scripts and algorithms for analog IC
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all project deliverables are met. Undertake these responsibilities in the project: Conduct technology review of sensor technology Develop algorithms/models for engine health monitoring Develop prototype
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work with our team to conduct research on the development of image analysis algorithms and AI methods for hardware security evaluation. The roles of this position include: Study literatures on multi
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Processing and Machine Learning to develop signal processing and machine learning algorithms and methods for drone swarms. The role will focus on visual localization techniques. Key Responsibilities: Develop
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the development of integrated sensor arrays through innovative materials design and validation techniques. This role supports NTU’s strategic direction in cutting-edge sensor research by contributing