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schools in the world. For more details, please view https://www.ntu.edu.sg/mae/research . We are looking for a Research Fellow to support research project. The role will focus on ultrasonic tomographic
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industry and international partners. For more details, please view https://www.ntu.edu.sg/atmri . We are looking for a Research Fellow to conduct research on air traffic management (ATM) algorithms and data
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Materials, Bioinspired Materials and Sustainable Materials. For more details, please view https://www.ntu.edu.sg/mse/research . The Decarbonisation Programme “Singapore Max-Planck Alliance for the Sustainable
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development, including Python, model integration, and system architecture design. Excellent communication and leadership skills, with prior experience in mentoring students or leading small teams. PhD degree in
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Materials, Bioinspired Materials and Sustainable Materials. For more details, please view https://www.ntu.edu.sg/mse/research . The Decarbonisation Programme “Singapore Max-Planck Alliance for the Sustainable
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records at the TRUST platform (https://trustplatform.sg/) . We are inviting a motivated Research Fellow to join our PRECISE-SG100K collaboration to work on the dataset (https://www.npm.sg/phase-ii-precise
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records at the TRUST platform (https://trustplatform.sg/) . Large-scale proteomics data have also been generated for these individuals. We are inviting a motivated Research Fellow to join our PRECISE-SG100K
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maintenance of equipment. Job Requirements Bachelor’s or Master’s degree in Computer Science, Artificial Intelligence, Software Engineering, or a related field. Strong programming proficiency in Python and/or C
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(Kubernetes), serverless computing, and REST API development. Proficient in Python, with basic experience in machine learning or computer vision libraries; familiarity with Vision-Language Models (e.g., CLIP
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. Proficiency in data analysis software (e.g., R, MATLAB, SPSS, Primer, Python). Experience with analytical techniques such as ANOVA, PCA, Regression, and Multidimensional Scaling (MDS). Experience in ecosystem