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, computational biology and biostatistics Experience in developing strategies to remove HCP, HCD and other impurities in compliance with phase I manufacturing and regulatory requirements. Lead downstream mRNA
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Bayesian modeling and machine learning using large longitudinal biomedical data, including electronic health records and mobile health data. The position will be funded by Samuel I. Berchuck, PhD who holds
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) to develop computational methods and also collaborate with other groups in quantitative genomics areas in and outside Duke University. Preferred qualifications: PhD (completed in the last 1-3 years or PhD
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will serve under the guidance of DPHS and DCRI faculty members and other senior scientists and will have the opportunity to lead and participate in a wide range of studies. Qualifications: PhD
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of appointment. · Must hold a PhD degree in biostatistics, statistics, computer science, computational biology, applied mathematics, or a related field. · Demonstrate a strong interest in an academic