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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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, and use smart phone apps to collect passive and active data using a prospective observational cohort study design. We will use this data to develop and validate a personalised risk prediction algorithm
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-modal fusion techniques for localization and mapping; (b) develop and implement algorithms for autonomous robots; (c) design and execute experiments to validate and refine algorithms and systems; (d
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Driven Discovery. Job Responsibilities: Analyze biomedical data with minimal supervision by performing advanced analysis, algorithm implementation, programming, and quality check. Assist senior analysts
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harness advanced techniques such as machine learning, optimization algorithms, and sensitivity analysis to automate and enhance the mode selection process. The result will be a scalable methodology that
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algorithms and AI methods for hardware security evaluation. The roles of this position include: Study literatures on PCB security evaluation, PCB multi-modal image analysis, and datasheet parsing. Data
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Responsibilities: Conduct in-depth research in sublinear time and learning augmented algorithms. Design, develop, and implement novel algorithms and models. Publish research findings in leading international
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Models with Algorithmic Reasoning Tasks We are seeking a postdoctoral researcher to contribute to our lab’s mission of aligning machine learning (ML) models with algorithmic reasoning tasks. Our goal is to
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meaning from data. Designing machine learning algorithms and undertaking testing for: predictive maintenance. operational performance and cost optimization. failure prevention and timely reparation of Aids
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qualification; (b) strong background in extensive model optimisation on machine learning algorithm; and (c) good communication skill in English. Applicants are invited to contact Prof. Kay Chen Tan