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Field
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comprise both the development of bioinformatics pipelines and the application of novel machine learning methods for interpreting microbiome and host ‘omics data from faecal, intestinal biopsy and saliva
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-seq datasets, and applying advanced statistical and machine-learning methods (AI/ML) to extract novel biological insights that drive our translational and fundamental research programmes. In
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mission is to innovate with industry, through an integrated applied learning and research approach, so as to contribute to the economy and society. Singapore is the small city with a big dream. We are home
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or machine learning to complex data. The successful candidate will have (or be nearing completion of) a PhD in a relevant field such as polymer science, materials engineering, or mechanical engineering
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and machine-learning methods (AI/ML) to extract novel biological insights that drive our translational and fundamental research programmes. In addition to your research leadership, you will play a
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experience in spatial analysis and/or machine learning methods, and an interest in applying these tools to urban and housing policy questions. The Fellow should demonstrate potential for producing high-quality
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with physical objects/environments, and audio rather than video based AR can help enhance memory/learning Humanizing Computer Mediated Communication: Synthesizing co-presence - What does it mean to feel
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Bezares (numerical relativity), Dr Stephen Green (gravitational waves, data analysis including machine learning, black holes), Dr Laura Sberna (gravitational waves, black holes, and environmental effects
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with physical objects/environments, and audio rather than video based AR can help enhance memory/learning Humanizing Computer Mediated Communication: Synthesizing co-presence - What does it mean to feel
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Machine learning/AI based classifiers Proficiency in coding using R and Python and other similar languages High level analytical capability Ability to communicate complex information clearly Informal