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data science - neuroscience and neural engineering - bio-statistics and AI-healthcare - smart/semi-conductor manufacturing - AI/robotics/autonomous systems - aerospace and microelectronics engineering
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performance. Applicants should possess a Ph.D. degree in Chemistry, Material Science, Microelectronics, or other relevant disciplines. The candidates shall have strong background in the field of organic
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engineering bio-statistics and AI-healthcare smart/semi-conductor manufacturing AI/robotics/autonomous systems aerospace and microelectronics engineering energy generation and storage digital business and
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microphotonics/microelectronics and quantum technology. Candidates will be responsible for both research and teaching. They are expected to teach courses at the undergraduate and postgraduate levels, specifically
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engineering bio-statistics and AI-healthcare smart/semi-conductor manufacturing AI/robotics/autonomous systems aerospace and microelectronics engineering energy generation and storage digital business and
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engineering bio-statistics and AI-healthcare smart/semi-conductor manufacturing AI/robotics/autonomous systems aerospace and microelectronics engineering energy generation and storage digital business and
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microelectronics engineering • energy generation and storage • digital business and innovation management • fintech and business analytics • computational social sciences • digital humanities
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engineering bio-statistics and AI-healthcare smart/semi-conductor manufacturing AI/robotics/autonomous systems aerospace and microelectronics engineering energy generation and storage digital business and
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manufacturing AI/robotics/autonomous systems aerospace and microelectronics engineering energy generation and storage digital business and innovation management fintech and business analytics computational
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engineering bio-statistics and AI-healthcare smart/semi-conductor manufacturing AI/robotics/autonomous systems aerospace and microelectronics engineering energy generation and storage digital business and