Post Doctoral Fellow - Pharmaceutical Health Outcomes and Policy (INTERNAL) - (497061 )

piece of research equipment. 4. May review and evaluate the effectiveness of personnel. 5. May plan for and assign personnel to projects under control. 6. Operates with latitude for unreviewed action. 7. May receive general supervision conferring with higher levels only in unusual situations. 8. Performs other job-related duties as required. The Population Health Outcomes and Pharmacoepidemiology Education and Research Center (P-HOPER Center) and Department of Pharmaceutical Health Outcomes and Policy (PHOP) at the University of Houston, College of Pharmacy, invite applications for a full-time postdoctoral fellowship focused on developing and applying methods for estimating the causal treatment effects on health outcomes using large health data. The Mission of the P-HOPER Center is to conduct innovative population health outcomes research and offer educational programs that impact both the region and the nation. The University of Houston is a Carnegie-designated Tier One public research university and a member institution of the world-renowned Texas Medical Center, home to leading clinical and academic programs. UH is also one of the most culturally and ethnically diverse public universities in the nation, with over 40,000 students. This position offers a unique opportunity to work with real-world data and modern causal inference methods to inform clinical decision-making. Ongoing projects focus on the comparative effectiveness of drug therapies on using large-scale observational electronic health record data and local electronic health record data. The fellow’s responsibilities include analyzing large-scale observational electronic health records and claims data (e.g., Medicare), leading manuscript preparation, and presenting findings at national and international conferences. The position is a two-year, full-time postdoctoral fellowship with competitive compensation and potential for renewal based on performance and funding availability. Qualifications: · Ph.D. in Pharmaceutical health outcomes, (Pharmaco)epidemiology, Biostatistics, or a related field. · Strong capabilities in quantitative healthcare data analysis (i.e., medical claims data, electronic medical records data, or registry data) · Expertise in or a strong interest in machine learning and deep learning algorithms · Research and publication experience in health outcomes research Application Materials: · CV · Cover letter · Contact information for three references. If you are interested, please send your application materials to Dr. Tiansheng Wang at tianwang@uh.edu MQ: Requires singular knowledge of a specialized advanced professional discipline or the highest level of general business knowledge, normally acquired through attainment of a directly job-related terminal degree or equivalent formal training in a recognized field of specialization that is directly related to the type of work being performed. No experience is required.

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