122 parallel-processing-bioinformatics Fellowship positions at Nanyang Technological University
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and development in the chemical conversion and valorization of hazardous waste streams, focusing on complex, reactive materials. Involves process design, optimization, and scale-up, including reaction
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the environmental performance of established and emerging processes. This role includes designing and conducting cradle-to-gate and cradle-to-grave LCAs, building life cycle inventory (LCI) datasets, and integrating
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organizational and interpersonal communications with excellent written, oral communication and computer skills. A team player who is able to prioritize, multi-task and work collaboratively in a diverse workforce
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framework on how to build up a generic framework to use learning-assisted approach to solve various optimization problems Develop mathematical modeling framework to find the optimal operation strategy Conduct
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plasma process equipment. Characterize the influence of magnetic field on plasma flow. Conducts various design experiments to refine processes. Optimize vacuum coating processes, and leading R&D efforts in
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communication, or signal processing. Proficiency in programming languages like Python, MATLAB, or C++, and experience with AI/ML frameworks like TensorFlow, PyTorch, or scikit-learn. A proven track record of
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the structure and functions of the human brain, with particular emphasis on both normal and pathological cognitive processes. Located in the Experimental Medicine Building on NTU’s main campus, CoNiC is equipped
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. The successful candidate will take technical ownership of thin film deposition, materials characterization, and process innovation, contributing both strategic insight and hands-on leadership to research programs
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multidisciplinary team driving transformative sensing technologies. Key Responsibilities: Develop and optimize fabrication processes for sensor arrays based on 2D materials (e.g., graphene, MoS₂), including flexible
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, electrical & electronic engineering, or equivalent. Background knowledge in signal representation/processing, visual data compression, and data-driven and machine learning/analysis. Prior research experience