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well as experience in applying deep learning and machine learning algorithms for pathogen identification, drug target prediction, antimicrobial drug discovery, and/or protein-protein interaction studies. They should
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to structural biology, protein engineering, machine learning, molecular cloning, in vivo experiments, and/or CRISPR technology. Candidates must exhibit a strong command of written and spoken English, and
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such as machine learning, programming, big data analytics, statistics, social network analysis, natural language processing, and population analysis. The appointee will work on the Master of Social Sciences
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. Requirements A Ph.D. in data science, statistics, psychology, public health, social sciences, or related disciplines. Proficiency in statistical analysis, data mining, predictive modeling, and machine learning
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Experience in image analysis packages such as Freesurfer, FSL, SPM, or 3DSlicer, or using machine learning or artificial intelligence models would be advantageous What We Offer The appointee would be exposed
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closely related data-analytics discipline. The Faculty is particularly interested in those who conduct high-quality scholarly research and are able to teach courses in business analytics, machine learning
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debriefing; developing pedagogical approaches and materials to cater for the learning diversity of multicultural students; promoting learning and teaching (L&T) with assessment data; sharing school-based
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data science, statistics, psychology, public health, social sciences, or related disciplines. Proficiency in statistical analysis, data mining, predictive modeling, and machine learning algorithms
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. Knowledge and skills in mathematics, biostatistics, or advanced statistical techniques in clinical research, database management, and machine learning (AI) will be taken into account. They should have
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, proactive facility management, building/city health check, and next-generation BIM and digital twins. Having expertise in leveraging advanced digital methods, big data analytics, machine learning, generative