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management tools. This role involves designing and executing large-scale epidemiological studies using EHR data, overseeing clinical data annotation/processing from public and Hospital Authority sources, and
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of substitution models using large dataset, successful applicants must then have a PhD and demonstrated experience in discrete choice models, machine learning techniques, big data, and optimization
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applicant must hold a PhD/DPhil in a relevant subject. They must have peer-reviewed publications using data science approaches, for example, genetic analysis, including Mendelian randomisation and genetic co
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for more information. About you To be successful in this role, we are looking for candidates to have the following skills and experience: Essential criteria PhD degree in Engineering, Computer
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19.5 hours per week. Required Education and Experience: Appropriate PhD in a related field No experience required Required Knowledge, Skills, and Abilities: Excellent verbal and written skills
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neuro-adaptability with changes in cortical manifestations during an intervention (e.g., non-invasive brain stimulation) for symptom reduction. Large-scale data analysis (e.g. machine-learning) will
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to the ongoing research in Prof. Marcotti’s laboratory by designing, developing and performing experiments, data analysis and disseminating the findings by writing articles and by presenting findings
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develop innovative solutions based on the analysis of urban data (big data, IoT, GIS) to monitor and improve public health. You will contribute to modeling smart cities with a focus on health and designing
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combine large-scale data, computational methods, and clearly articulated social-science theories to improve our understanding of society. Recent advances in machine learning, natural language processing
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data (transcriptomics, proteomics and metabolomics), from a large collection of well-characterized samples to identify novel biomarker and causal and druggable targets. We are seeking a motivated