664 parallel-computing-numerical-methods positions at National University of Singapore
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environmental design, human well-being, and quantitative assessment methods. Experience with landscape visualisations, data analysis, computational modelling, information modelling, or human-centred research
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opportunity to be involved in the development and optimization of mass spectrometry-based methods for biomonitoring. You do not need to have a background in academic research. In fact, we would be very keen to
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dedicated to technology such as state-of-the-art light microscopy, nano- and micro- fabrication, and computing. We are seeking a Research Fellow with expertise in transmission electron microscopy (TEM
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background and keen to delve into heat health research are strongly encouraged to apply as well). Experience in statistics, data analysis and visualisation software (e.g. SPSS, Power BI), and computer
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wearable devices. Investigate new materials and fabrication methods to improve the flexibility, efficiency, and scalability of wearable electronics. Collaborate with multidisciplinary teams, including
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wearable devices. Investigate new materials and fabrication methods to improve the flexibility, efficiency, and scalability of wearable electronics. Collaborate with multidisciplinary teams, including
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discipline (e.g. urban planning, geographic information science, computer science). Current master students are eligible to apply as well, provided that they are in the final stage of their studies and that
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discipline (e.g. urban planning, geographic information science, computer science). Current master students are eligible to apply as well, provided that they are in the final stage of their studies and that
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Program Team and Instructors to schedule and create video assets for course program. Assists in post-production work, including preparing graphics, inserting subtitles, syncing of audio files, creating
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findings in peer-reviewed journal, - assisting the PI in other day-to-day tasks as required. Candidate must: - possess EITHER at least a Bachelor’s Degree in Computer Science, Mathematics, Statistics