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) Develop digital twin models for ventilators using machine learning and AI modelling techniques, b) Run simulations to obtain ventilator’s performance in varying conditions, c) Draw insights through
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Job Description Job Title : Research Associate in AI and Machine Learning Department : Saw Swee Hock School of Public Health Institution : National University of Singapore Position Type : Full-time
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on the theory and applications of machine learning. The position emphasizes advancements in artificial intelligence and operations research, supporting Singapore's goal of using technology for societal
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and/or machine learning. The College of Science seeks a diverse and inclusive workforce and is committed to equality of opportunity. We welcome applications from all and recruit on the basis of merit
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of machine learning interpretability solutions in production. Key Responsibilities: Implement machine learning interpretability tools and pipeline to be included in the future machine learning interpretability
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language processing (NLP), and multimodal learning (ML). Critically evaluate existing literature and propose new ideas under supervision Write papers and present the research work to a wide audience Job Requirements
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that are relevant to industry demands while working on research projects in SIT. The Candidate will be working on a sustainability and AI project, coupling physics-based models and data driven machine learning
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undertake research in computer vision and machine learning. To produce research reports and/or publications as required by the funding body or for dissemination to the wider academic community. To attend
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development of novel signal processing and machine learning methods for Brain Computer Interface (BCI)-based motor imagery kinematics decoding. Development of real-time Electroencephalogram (EEG) data
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) will be responsible to assist in developing techniques such as AI/machine learning/deep learning , to model the normal behaviours and detect anomalies in SDN. The work involves experimentation with a