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Python) Experience in analyzing large and/or complex datasets Interest in quantifying uncertainties for computer models and/or climate predictions Ability to work in a team Ability to communicate orally in
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Description Job Responsibilities -Analyze and interpret metagenomic data to investigate and identify often divergent viral genome sequences. -Collect, reconstruct and analyze large datasets obtain by cryo
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genomics, with cutting-edge methods, large data sets and good resources A creative role combining a high degree of autonomy with mentorship from Dr. Lappalainen and interactions with colleagues in the lab
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statistical and computational methods designed to use “big data” and to address questions of direct or indirect relevance to common complex diseases and disorders. The appointee will join the group of Professor
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of Medicaid, Medicare, and private insurance data and the application of social science theory and advanced statistical techniques in large data sets. Statement Posting Details Special Instructions
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of a team performing both ex-vivo and large animal in-vivo studies) of catheter-based cardiac/myocardial ablation. The clinical applications investigated will include ventricular tachycardia and
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undergraduate or graduate students, if appropriate. Additional Information The ideal candidate should be an independent, solution-oriented thinker with a strong background in processing very large data sets
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engineering, or a related field. · Strong background in machine learning or data analytics and hands-on experience handling big data. · At least one year of research experience in transportation
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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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to submitting your application, please review and update (if necessary) the information in your candidate profile as it will transfer to your application. Job Title: Post Doctoral Scholar Department: Engineering