172 parallel-processing-bioinformatics research jobs at Nanyang Technological University
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and inference processes Conduct experiments to compare with comprehensive baselines and validate results Job Requirements: Preferably Master / Bachelor’s degree in Computer Engineering, Computer
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of the designed algorithms and systems. Help with research presentation works such as high-quality paper writing. Job Requirements: Preferably Bachelor’s degree in Computer Engineering, Computer
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. Perform any other duties relevant to the research programme. Job Requirements: PhD in Computer Engineering, Computer Science, Electronics Engineering or equivalent. Independent, highly analytical, proactive
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by using explainable AI To develop generative AI techniques to design novel biologics for cancer Job Requirements: Preferably PhD in Computer Engineering, Computer Science, Electronics Engineering or
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on the research results. Job Requirements: Preferably Bachelor’s degree in Computer Engineering, Computer Science, Electronics Engineering or equivalent. Independent, highly analytical, proactive and a team player
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journals such as S&P, USENIX, SIGMOD, VLDB, NeurIPS, ICML, AAAI, or ICLR. Job Requirements: A PhD degree in computer science, computer engineering, mathematics, statistics, or a related discipline with a
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of the designed algorithms and systems. Help with research presentation works such as high-quality paper writing. Job Requirements: Preferably bachelor's degree in Computer Engineering, Computer
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Fellow to lead a project titled Closed-Loop Advanced Manufacturing Process (c-LAMP) under NTU. The role will focus on developing a modularized and energy-efficient treatment process, ie. electrochemical
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of the designed algorithms and systems. Help with research presentation works such as high-quality paper writing. Job Requirements: Preferably PhD in Computer Engineering, Computer Science, Electronics Engineering
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, early life antibiotic use, ultra-processed foods, and microbiome changes. The research team also develops machine learning models to predict cancer risk from longitudinal medical data. For more details