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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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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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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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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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++, Python, LabView) and firmware development. Working experience with IoT, data analytics, artificial intelligence, machine learning, etc. Extensive hands-on experience and knowledge of industry practices
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skills. Research experience in coastal and ocean waves is preferred. Excellent communication (verbal and written) and teamwork abilities Proficiency in machine learning will be an advantage Key
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fabrication and able to use and teach use of lathe, milling machine and similar workshop machinery. Hands-on competence in CAD, CAM and CNC programming. CNC machining experience, 3 axis and ideally experience
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will also work with team members within the consortium in generating necessary data required for developing a machine learning model for storm surge prediction. Key Responsibilities Participate in and
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-informed neural network, transfer learning, and edge intelligence) for battery management systems that lead to publications in top-tier international conferences and journals, as well as real-world
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-informed neural network, transfer learning, and edge intelligence) for battery management systems that lead to publications in top-tier international conferences and journals, as well as real-world