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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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). Applying advanced statistical and machine learning methods (e.g., predictive modelling, clustering, multivariate integration) to large-scale time series and sensor datasets. Contributing to the development
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machine learning methods to the analysis of large-scale astronomical datasets, with a particular emphasis on time-domain astronomy. Research directions will be flexible and shaped according to mutual
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for machine learning and artificial intelligence, with a strong emphasis on developing and applying models such as LSTM and other time-series analyses to predict the longevity and behaviour of bioactive
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. • The ability to work independently and collaboratively within a multidisciplinary team. • Strong writing, critical thinking, communication, and presentation skills. • Experience in Machine Learning is a
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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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., • Interest in developing risk prediction models via deep learning/machine learning. • Have strong background in DL, EEG data and programming for the implementation of proposed methods. Apply now
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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. Experts in
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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. Experts in
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. Qualifications/Requirements Qualifications / Discipline: - PhD from a reputable institution in Physics, Bio-imaging, Computer Science, or a scientific domain closely related to Machine Learning. - The candidate