33 phd-position-in-data-modeling Fellowship positions at National University of Singapore
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advancing impactful Health Services Research. The successful candidate will support and/or lead research projects focused on improving patient care delivery, evaluating new care models, and informing health
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requirements: PhD Degree in Computer Science, Artificial Intelligence, Machine Learning, Data Science, or a related field, obtained within the last five year Research Experience in one or more of the following
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behavioral experiments to address these questions using the PD mouse models and iPSC derived human patient neurons In addition to PD, we are also interested in investigating the pathogenic mechanisms
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behavioral experiments to address these questions using the PD mouse models and iPSC derived human patient neurons In addition to PD, we are also interested in investigating the pathogenic mechanisms
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competitive salary (> S$70k/year) for the position with the consideration of years of experience postgraduate. The duties of the Postdoc include: Collect and process remote sensing data relevant
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well as academics. CIL is soliciting applications for several Post-Doctoral Fellowship positions commencing in August / September 2025. Initial appointments will be for one year (with the possibility of extension
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the development of laboratory and epidemiologic capacity, training scientists and physicians from partnering countries to make Singapore a viable surveillance hub for emerging infectious diseases. The position
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RESEARCH FELLOW IN ARI(TRANSITION RISKS IN IMPLEMENTING FOREST CARBON INITIATIVES IN SOUTHEAST ASIA)
considered. For further enquiries about the positions, please contact Professor David Taylor (geodmt@nus.edu.sg ). More Information Location: Kent Ridge Campus Organization: Asia Research Institute Department
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imaging and viral/drug/ASO delivery. Identify and develop suitable approaches for the collection and analysis of data. Maintain accurate and complete records of all findings, and ensure the validity and
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such falls prevention programmes at a national level. The successful candidate will lead and coordinate data collection efforts for cost-effectiveness analyses, including obtaining and harmonising healthcare