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and engineering in the context of Singapore’s coast to build strong features that can be used to predict occurrences of storm surges Implement and test different machine-learning models to evaluate
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the project by: analyzing data on the key protein properties generated by our experimental team, using data analytics or machine learning techniques, linking protein sequences, mass spectrometry data and
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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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techniques, sensor and operation data fusion, data analytics and machine learning algorithms. The primary responsibility of this role is to deliver the program objectives for remote pilotage. Key
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machine learning algorithms for electrical vessels condition monitoring, fault diagnosis and early fault prediction. The primary responsibility of this role is to deliver on Ship-level intelligent Equipment
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. Experienced in developing machine learning and generative AI solutions for deployment into production. Strong proficiency in Python and AI frameworks (TensorFlow, PyTorch, Keras) Strong programming skills in
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, data analytics, artificial intelligence, machine learning, etc. will be advantageous. Work independently, as well as within a team, to ensure that the project can meet the milestones adhering
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As a University of Applied Learning, SIT works closely with industry in our research pursuits. Our research staff will have the opportunity to be equipped with applied research skill sets
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. These projects may include generative AI, AI and Machine Learning and Business Process Automation (BPA) related projects. Provide documentation support in the designing, developing, implementing, and monitoring
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is mandatory. • Experience in the development of novel signal processing and machine learning algorithms for Electroencephalography (EEG)-based Brain Computer Interface. • Proficiency in programming