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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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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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machine control for smart manufacturing as well as publications in top-tier international conferences and journals, as well as real-world implementations. If interested, please apply with your resume
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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
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experience may also be considered. Previous experience with DES / Deep learning using neural networks / DRL / Explainable machine learning / AnyLogic would be advantageous. Interest and enthusiasm
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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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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