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analysis, and proficiency in statistical and computer modelling software (e.g. R, Python, Matlab, and C++) would be advantageous. The appointee will work with a research team to study the methodologies
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infectious disease data using statistical and/or mathematical approaches would be highly desirable. Experience in statistical analysis, and proficiency in statistical and computer modelling software (e.g. R
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Post-doctoral Fellow/Senior Research Assistant in the Centre for Information Technology in Education
linear regression, mediation analysis, multilevel modeling, and/or latent variable models. Experience in managing and analyzing large datasets, and the use of generative AI tools for research purposes
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analysis, and proficiency in statistical and computer modelling software (e.g. R, Python, Matlab, and C++) would be advantageous. The appointee will work with a research team to study the methodologies
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the analysis of large and complex datasets; iv) excellent written and oral communication skills; and v) the ability to work independently as well as in collaboration with a multidisciplinary team. Proficiency
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Post-doctoral Fellow/Senior Research Assistant in the Centre for Information Technology in Education
innovative methods of assessment and/or advanced statistical methods, such as multiple linear regression, mediation analysis, multilevel modeling, and/or latent variable models. Experience in managing and
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experimental, writing, and communication skills. Preference will be given to candidates with research experience in epigenetics, stem cell reprogramming, neural development, disease modelling using human iPSCs
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with research experience in epigenetics, stem cell reprogramming, neural development, disease modelling using human iPSCs, and/or genomic medicine. In particular, we seek applicants with expertise in
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an outstanding research track record and extensive expertise in cancer bioinformatics, cancer biology, cancer immunology, deep learning models and/or artificial intelligence, as well as hands-on experience with
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immunology, deep learning models and/or artificial intelligence, as well as hands-on experience with cell culture, cellular/molecular biology, and animal studies. The ideal candidate should be self-motivated