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for engineering biology. GBI researchers will also be supported by cutting edge facilities including mass spectrometry, flow cytometry, sequencing, automation, scientific computing, bioinformatics, and machine
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implementing innovative technologies and strategies driven by significant advances in computational biology, including bioinformatics, systems biology, and machine learning applications. The Head is expected
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(EHR), health information exchanges, and data analysis software. Experience with health IT innovation, including working with artificial intelligence, machine learning, telemedicine, or mobile health
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. Its human size fosters close interaction between students and lecturers, creating a personal atmosphere. With 1,600 members of academic staff for 6,700+ students and 1,000+ PhD candidates, students feel
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. Experience with applied computational methods and machine learning is preferred but not essential. Postdoctoral research experience is preferred but not essential. A thorough understanding of the fundamentals