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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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) 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
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, exploring methods of data analysis, cleaning and pre-processing of raw data, modelling data using Machine Learning/Deep Learning techniques, and sharing of insights to stakeholders using visualizations. Our
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resources engineering, optimization, seasonal forecasting, machine learning, or from similar programs. • Extensive experience in developing complex computer codes, e.g. in Python, R, or Shell. • Ability
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the cutting-edge field of fast-paced solar forecasting and resource assessment. The daily work routine will involve developing various algorithms, including but not limited to machine-learning models, satellite
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& Innovation) with the prototyping for their projects. The candidate needs to be able to teach students best engineering practices. In addition, he/she has the ability to identify problems with the students
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Job Description • Drive a range of NUS-owned vehicles (e.g. saloon car, MPV, mini-bus, panel van, pick-up and lorry) • Ferry NUS senior management, University guests, staff and students with special
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through coursework (especially math-intensive courses) and projects during his/her undergraduate and master’s studies. • Proficient in C++ or Python. Familiar with machine-learning tools and packages