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Osmosis (NF/RO) Membrane for Industrial Separation and Purification Application” Key Responsibilities: Integrating Machine Learning (ML) with Molecular Dynamics (MD) to predict phase-separation dynamics and
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at NTU are looking for a Research Fellow (RF) to carry out research in probabilistic machine learning and GenAI, by exploring cutting-edge approaches such as sequence model design, continual learning
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areas: wireless security, wireless communications, AI/machine learning for communications, covert communications, signal processing, and/or RF design. Ability to conduct research independently and
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system. Job Requirements: Possess a PhD in Computer Engineering, Computer Science, Electronics Engineering or equivalent. Independent, highly analytical, proactive and a team player Solid background in
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relationships and apply data-driven or machine learning approaches to guide molecular design and accelerate materials discovery Collaborate with internal and external stakeholders, including computational, data
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methods in meteorology (atmospheric data assimilation). This contributes to the cutting-edge research expertise of the College and the University in the strategic areas of Machine Learning, Statistical Data
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academic institutions to translate research into viable solutions. Job Requirements: Preferably PhD in computer engineering, Computer Science, Electronics Engineering or equivalent. Independent, highly
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external fundings when appropriate. Job Requirements: Preferably PhD in Computer Engineering, Computer Science, Electronics Engineering or equivalent. Independent, highly analytical, proactive and a team
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, and laboratory operations. Job Requirements: PhD in Electrical Engineering, Computer Engineering, Physics, or a closely related discipline. At least three years of relevant research experience in
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good academic publication record Familiar with a few key engineering software such as MATLAB, Python, R-language, and ArcGIS, etc. Good to have knowledge of network analysis, machine learning, neural