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data from existing cohorts and national registries, applying novel machine learning methods. The specific work tasks will include data management of large studies, scientific work related to the topics
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health, epidemiology, biostatistics, health services research, general practice, and global health. The Department is an inclusive workplace hosting a large group of faculty, postdocs, and PhD students
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developing new machine learning methodologies that tackle unique computational problems in healthcare applications. We use large real-world complex datasets, including data extracted from electronic health
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postdoctoral researcher. You will work in a large team of skilled and motivated researchers (PhD students and postdocs), technicians and students that are developing and applying state of the art research tools
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, creative start-ups, big data, big ambitions, hands-on learning, and a whole lot of robots, CMU doesn’t imagine the future, we invent it. If you’re passionate about joining a community that challenges the
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discovery from large scale amplicon sequencing data, development of qPCR primers for specific predator, pathogen, or other organismal groups, and large-scale microcosm experiments for predation of pathogens
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, or statistics. Expertise in data science with large astronomical data sets or simulations. Excellent verbal and written communication skills Preferred qualifications: Hands-on ML experience for scientific
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at CRAG (from basic science to applied research using plant experimental model systems, crops and farm animals) make extensive use of genomic technologies and large sets of genetic and genomic data (https
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for analysis of health record data for patient diagnosis and outcome prediction. Perform large-scale querying and analysis of clinical health record databases. Engage with clinical collaborators, to place the
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generic project proposals which were generated by large language models such as ChatGPT will not be considered. Candidates for postdoctoral positions are expected to have completed a PhD (or equivalent