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of Singapore (NUS) invites applications for a Senior Bioinformatician to support and lead advanced research with clinical and translational impact, driving the generation of high-quality data and analyses
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footprint. Its holistic approach will help to secure a brighter, more sustainable future for humanity. We are looking for a Research Engineer to support innovative research in federated learning and computer
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for academic and administrative functions to ensure seamless operations. Process all finance-related claims for UG and PG units, Reporting & Data Management Prepare and maintain accurate faculty records
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data in accordance with study protocols. Perform accurate and timely data entry, ensuring data integrity and confidentiality. Qualifications Preferably with dental training or relevant experience in
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administrative support, and undertake project management responsibilities to ensure the timely and high-quality delivery of project outputs. Key responsibilities: Conduct literature reviews, data collection and
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partnerships with industry partners. Monitor the progress of stakeholder engagement initiatives, collect data and conduct analyses to evaluate the impact and effectiveness of initiatives. Present the collated
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to the applications of mathematics in cryptography, computing, business, and finance. PAP covers many areas of fundamental and applied physics, including quantum information, condensed matter physics, biophysics, and
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the Open Science and Research Services function with the Office of Information, Knowledge and Library Services (OIKLS). The successful candidate will provide research services to support NTU researchers in
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Assistant (Senior) or Research Associate to join our team at CARE. This role offers an excellent opportunity to gain hands-on experience in project management, quantitative research, data analysis, and
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Corporate Laboratory is seeking to hire a Research Associate. The selected candidate will focuses on analyzing equipment degradation time-series data and developing forecasting workflows using statistical