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Research Fellow in Atomically Thin Quantum Materials for Low-Energy Electronics Job No.: 694378 Location: Clayton campus Employment Type: Full-time Duration: 2.5 years fixed-term appointment
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Materials, Bioinspired Materials and Sustainable Materials. For more details, please view https://www.ntu.edu.sg/mse/research . We are seeking a highly motivated and interdisciplinary Research Fellow to
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, Materials Science, Applied Physics, or related field Experience in high-reliability microelectronics Familiar with micro-fabrication techniques and semiconductor processing Experience in conducting electrical
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University focused on advancing computer vision, multimodal AI, generative AI, and embodied AI. Founded in 2018, the lab has grown into a vibrant research group with around 40 members comprising faculty
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, their fabrication and characterisation in order to be translated to industry with our partners. This includes laboratory experimentation, critical evaluation and interpretation, computer-based theoretical modelling
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1. Possess a Ph. D Degree in Electrical Engineering with strong knowledge in semiconductor device technology and process. 2. Strong knowledge in semiconductor device physics. 3. At least 4 years in simulation, fabrication, and testing of semiconductor devices. 4. Proficient in...
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Location ESTEC, Noordwijk, Netherlands Our team and mission The Radiation and Component Reliability Section (TEC-EDR) and the Microelectronics Section (TEC-EDM) are part of the Avionics and EEE
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The Institute for Health Innovation & Technology (iHealthtech) at the National University of Singapore (NUS) was founded in 2017 to advance health through technological innovation. Focused on tackling clinical challenges, iHealthtech develops innovative health technologies, bridging the gap from...
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deployment enabling validation and demonstration of real-world applications. For more details, please view https://www.ntu.edu.sg/erian Purpose: We are seeking a Research Fellow to support research and
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collaborative and interdisciplinary activities. Job Requirements: Preferably PhD degree in Computer Engineering, Computer Science, Applied Mathematics or equivalent. Strong academic background in machine learning