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, documentation, and presentations) - essential for data analysis and communication with stakeholders Proficiency in hard skills, such as programming (Python, C++), machine learning frameworks (PyTorch, TensorFlow
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Proficiency in scientific programming and simulation tools (e.g., Python, MATLAB) Proven ability to conduct independent research, publish high-quality work, and collaborate effectively Strong written and oral
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Medical School. In August 2024, we welcomed our first intake of the NTU MBBS programme, that has been recently enhanced to include themes like precision medicine and Artificial Intelligence (AI) in
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Medical School. In August 2024, we welcomed our first intake of the NTU MBBS programme, that has been recently enhanced to include themes like precision medicine and Artificial Intelligence (AI) in
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distributed energy resources (DERs). Design & develop optimization algorithms/tools to plan the deployment of DERs such as energy storage systems (ESS), photovoltaic generations (PV), electric vehicle charging
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students involved in the project. To collaborate with industrial and academic partners. To perform any other duties related to the research program. Job Requirements: Preferably PhD in Computer Engineering
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learning/analysis. Prior research experience and track record in R&D and standardization. Prior experience in state-of-the-art AI techniques. Mastering of a programming language would be valued (e.g. Python
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model is employed to forecast renewable energy availability, providing crucial insights for the design optimization process. The ML-assisted operation tackles the dynamic optimization of parallel energy
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Medical School. In August 2024, we welcomed our first intake of the NTU MBBS programme, that has been recently enhanced to include themes like precision medicine and Artificial Intelligence (AI) in
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successful, support to build the portfolio towards a new Interdisciplinary Research Programme in tidal and other ocean energy resources. The Research Assistant / Research Fellow is to assist the ERI@N Program