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. Demonstrated experience in managing large-scale data sets and conducting health-related research studies. Strong analytical skills with proficiency in statistical software and data analysis tools, particularly
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research skills in methodological development and data analysis Strong organizational, interpersonal, and problem-solving skills Good teamwork with excellent communication and public relations skills
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analysis. We are looking for researchers to join a multi-disciplinary team carrying out research projects on a range of energy issues that are of concern to Singapore and the region. The Institute is
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these conditions. Independently carry out the design and execution of experimental research required by the research component of the project. Independently design, plan, and execute experimental research aligned
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assessment, early health technology assessment, and/or medical innovation development • Health economic modelling with Markov cohort model/ discrete event simulation • Data analysis or data management using
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or adaptive designs. • Proficiency in at least one of the following: R, Python, JavaScript, or other relevant data analysis or app development tools. • Familiarity with EMA, EMI, MRTs, or SMART designs is
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– Literature reviews and research writing. Phase 2 – Survey and experiment design, and IRB applications. Phase 3 – Data collection and pre-processing. Phase 4 – Data analysis and result tabulation. Phase 5
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the Principal Investigator (PI) in managing and executing the research project. Conduct literature reviews, data collection, and analysis using multimodal research methodologies. Design and implement experiments
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fluorescent microscopy, polarized light microscopy) and biochemical analytical methodologies (e.g. micro-FTIR, micro-XRD, micro-MRI, micro-CT and so on) Bio-sample preparation Literature review, data analysis
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methods for multi-omics data analysis. Potential projects may include developing methods for studying tumor microenvironment using spatial transcriptomics data, proteogenomics integrative analysis