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concordance and adverse health outcomes using large -scale healthcare datasets. Working collaboratively with clinicians, researchers, patient partners and data specialists to ensure scientific quality and
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protocols, and test hypotheses and analyse scientific data. You will be expected to contribute ideas for new research projects, develop ideas for generating research income, present detailed research
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successful in this role, you will hold (or be close to completing) a PhD/DPhil in machine learning, artificial intelligence, computer science, epidemiology, health data science, or a related quantitative
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applicable. Preferred Qualifications PhD in data science, and/or public health or related fields including health services research, health informatics, computer science. Experience in data analysis using
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to manage, organize, and back up large amounts of image and tabular data generated by program and collaborator labs. Other Requirements: -May have to work on the weekend and/or after normal hours. -Travel is
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employees, including 120 teachers and 120 PhD students. Approximately 5,000 undergraduate students take one or more courses at the department each year. You can find more information about us on the
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statistical and machine learning methods applied to large claims and electronic health record databases and multimodal data, including physiological waveforms and medical imaging. We foster a collaborative and
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of research investigating cancer risk and prevention. The appointee will work closely with Professor Ruth Travis, Dr Karl Smith-Byrne and other members of the research team, using large-scale epidemiological
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and spatial analysis techniques to large-scale spatial transcriptomics and imaging datasets, using tools such as MuSpAn to identify spatial biomarkers and uncover the biological mechanisms driving
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Position Details Position Information Recruitment/Posting Title Postdoctoral Associate Job Category Staff & Executive - Research (Laboratory/Non-Laboratory) Department CINJ - Pediatric Hematology