Position Summary: The Department of Public Health Sciences at the Medical University of South Carolina invites applications for a Research Associate in applied Bayesian methodology with a focus on medical informatics and public health research. The Research Associate will be supervised by Brian Neelon, PhD, Associate Professor of Biostatistics, and Dr. Leslie Lenert, Professor of Medicine and Chief Research Information Officer for the University.
Duties and Responsibilities: The Research Associate will apply methods originally developed in consumer research to help guide medical decision making. Specifically, the Research Associate will use Bayesian nonparametric models to cluster patients based on their treatment preferences. The results will subsequently be used to develop web-based systems to help inform patient choices. The research associate is expected to code computationally efficient Markov chain Monte Carlo algorithms for existing models, and to develop new methodology as part of a supervised program of research.
Qualifications: The selected candidate should have, or expect soon to have, a doctoral degree in Biostatistics, Statistics, or related quantitative field.
The candidate should have solid training in Bayesian statistical methods and excellent computation skills. Preference will be given to candidates with expertise in Bayesian nonparametrics, Bayesian computation, multivariate data analysis and machine learning. Competency with R statistical software is required, and experience with C++, Python, or similar programming languages is a plus. Strong oral and written communication skills are essential.
Application Information: Applicants should apply online at http://www.jobs.musc.edu/postings/33250 and include a cover letter detailing experience and research interests, a CV, and contact information for 2 to 3 professional references.
Appointment and Salary: This is a two-year position with year two dependent on the successful completion of year one. Salary will be commensurate with experience.
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Website: http://people.musc.edu/~brn200/
Application Deadline: Review of applications will begin immediately and continue until the position is filled.
Equal opportunity employer.
