Postdoctoral Scholar - Research Associate
About The Position
Our research group develops models and methodology for improving health policy decision-making using a variety of techniques, including stochastic modeling, optimization, simulation, dynamic programming, and others. We currently have several funded projects in collaboration with medical practitioners, with applications to periodontal disease, diabetes control, and infectious disease policy. Thus, in addition to the responsibilities listed below, the postdoctoral scholar may have the opportunity to work with clinical trial data and/or analyze electronic health record data from a large hospital system in Los Angeles, depending on interest, and can mentor students and participate in grant proposal development if desired.
Requirements
- Expertise in data analytics/statistics/machine learning for prediction: work with datasets to generate summary statistics, run regression analyses and predictive methods, assess performance and feature importance, visualize data.
- Experience with building individual-level simulations for health (microsimulation), including coding (developing new code and adapting existing code), model parameterization, model calibration/validation, and generating intervention output from simulated scenarios.
- Doctorate degree in health research and policy, management science, industrial engineering, operations research, statistics, machine learning, or related fields and have a strong research record.
- Strong writing and verbal communication skills are required, with the ability to communicate technical results and incorporate feedback to interdisciplinary collaborators.
Nice To Haves
- Experience with healthcare data is preferred but not required.
- Candidates with experience in other modeling methodologies (e.g., optimization, compartmental modeling, dynamic programming, etc.) are preferred but not required.
Responsibilities
- Use statistical and machine learning techniques to predict health outcomes in empirical data (longitudinal and cross-sectional)
- Build and modify individual-level simulations for determining the long-term cost and effectiveness of health interventions
- Regularly communicate findings to collaborators (including researchers from other research fields, clinicians, and health providers) and incorporate feedback
- Lead the research team in writing manuscripts and disseminating findings at scientific meetings
Benefits
- Excellent benefits and perks
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What This Job Offers
Job Type
Full-time
Career Level
Entry Level
Education Level
Ph.D. or professional degree
