Postdoctoral Fellow, College of Pharmacy, Dr. Kang lab

The University of Texas at Austin • Austin, TX

13d • Hybrid

About The Position

The Kang Research Group in the Division of Health Outcomes at The University of Texas College of Pharmacy invites applicants for a postdoctoral fellowship aimed at preparing independent academic researchers in health outcomes research and health disparities. The selected fellow will work primarily with Dr. Hyeun Ah Kang, whose research focuses on assessing health policy impacts on vulnerable populations, evaluating treatment and guideline adherence, analyzing health care resource utilization and costs, identifying predictors of clinical and economic outcomes, and examining health disparities using large, real-world databases (e.g., Texas Medicaid, Merative™ MarketScan®, and the Medical Expenditure Panel Survey [MEPS], with a particular focus on sickle cell disease, opioid utilization, and cancer disparities).

Requirements

• PhD or equivalent degree in health outcomes research, health economics, public health, or a related field, earned within the past three years
• Strong database management and quantitative data analysis skills (SAS preferred)
• Experience with large health care data (e.g., public/private health insurance claims data, electronic health records, registry data, or national survey data)
• Experience with or willing to learn machine-learning techniques
• Strong critical thinking skills with the ability to solve problems
• Ability to work independently and in teams
• Excellent communication and writing skills
• Evidence of a publication record
• A strong work ethic

Nice To Haves

• Prior experience conducting health policy or health disparities research.
• Experience analyzing medication utilization, adherence, or health care costs.
• Exposure to causal inference methods, quasi-experimental designs, or advanced statistical techniques.
• Experience preparing grant applications.
• Demonstrated ability to manage multiple projects and meet deadlines in an academic research environment.

Responsibilities

• Design and conduct independent and collaborative research studies in health outcomes research, health policy, and health disparities, with a focus on vulnerable populations.
• Lead and contribute to all phases of the research process, including study conceptualization, protocol development, data acquisition, data management, statistical analysis, and interpretation of results.
• Analyze large, real-world health care databases (e.g., Medicaid claims, commercial claims, and national survey data) using advanced quantitative methods, primarily in SAS, and incorporate emerging analytic approaches such as machine learning as appropriate.
• Evaluate the impact of health care policies, medication utilization patterns, treatment adherence, and clinical and economic outcomes, with emphasis on conditions such as sickle cell disease, opioid use, and cancer disparities.
• Prepare high-quality manuscripts for submission to peer-reviewed journals and contribute to the dissemination of findings through conference abstracts, posters, and oral presentations.
• Participate in grant development activities, including drafting specific aims, study designs, and analytic plans for external funding applications.
• Engage in scholarly activities such as literature reviews, seminars, workshops, and other professional activities to strengthen expertise in health outcomes research and scientific communication.
• Collaborate effectively with faculty, research staff, and interdisciplinary teams within and outside The University of Texas at Austin.
• Demonstrate increasing independence in research productivity while working closely with Dr. Kang for mentorship and career development.
• Other related duties as assigned.

Benefits

• insurance and Teachers Retirement System (TRS) retirement benefits
• paid vacation, sick and holiday time off
• access to employee professional development and wellness services
• the opportunity to qualify for the Public Service Loan Forgiveness (PSLF) federal program

What This Job Offers

• Job Type: Full-time
• Career Level: Entry Level
• Education Level: Ph.D. or professional degree