National Community Pharmacists Association
Postdoctoral Scholar - Research Associate (USC Schaeffer Center)
National Community Pharmacists Association, Los Angeles, California, United States, 90079
Position Overview:The University of Southern California's Leonard D. Schaeffer Center for Health Policy and Economics is now accepting applications for one or more Postdoctoral Fellowships in health policy, health economics, and health services research with a
specific focus on machine learning and data science applications
in health economics and outcomes research (HEOR) and pharmacovigilance. This fellowship provides an excellent opportunity to enhance analytical skills and advance research agendas through both formal training and extensive collaboration with leading researchers.Postdoctoral scholars will serve as research trainees to enhance and develop their research competencies. Scholars will work directly with senior Faculty such as Drs. Dana Goldman, Julie Zissimopoulos, Daniel McFadden and Darius Lakdawalla. Responsibilities include planning, designing, and conducting complex research projects under the guidance of mentors. The role may involve both independent and collaborative work.This new call aims to attract talented individuals eager to contribute to the advancement of health policy and economics through innovative machine learning and biostatistical methodologies.Key Responsibilities:Collaborate with USC faculty on cutting-edge research projects in health economics and policy.Design, develop, and estimate health economic models to study the clinical benefits and economic value of new health interventions. Analyze individual patient-level data and other sources to parameterize these models.Apply interpretable machine learning techniques to the study of health economic models and the analysis of patient-level healthcare data.Produce high-impact research papers, such as those focusing on the value of Alzheimer's disease treatments.Eligibility Criteria:We invite scholars who have recently completed a Ph.D. in a relevant discipline such as biostatistics, computer science, data science, health economics, health policy, or public policy to apply. Candidates should possess robust data science and programming skills, including Python, and have a keen interest in applying interpretable machine-learning methods. Candidates should also have experience constructing and analyzing cost-effectiveness and/or other health simulation models.Minimum Qualifications:Education: Ph.D. or equivalent doctorate within the previous five years.Experience: 0-1 year of relevant research experience.Field of Expertise: Interpretable machine learning, data science, and health economics.Preferred Candidate Profile:Strong programming skills in Python.Experience building cost-effectiveness and health simulation models.Proficiency in interpretable machine learning techniques.Demonstrated ability to publish in peer-reviewed journals.Compensation and Duration:The annual base salary range for this full-time position is $75,000 - $100,000. When extending an offer of employment, the University of Southern California considers factors such as (but not limited to) the scope and responsibilities of the position, the candidate's work experience, education/training, key skills, internal peer equity, federal, state, and local laws, contractual stipulations, grant funding, as well as external market and organizational considerations.The fellowship provides a competitive stipend and other benefits for a 12-month fixed term, which may be renewed up to a maximum of two years. Hybrid work arrangement.Application Process:Please upload CV, cover letter, writing sample, one-page statement of research interest and recent reference letter(s) as a single combined PDF file. Python code samples may be requested during the interview process.Application Deadline:Applications will be considered as they are received until the position(s) is filled.
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specific focus on machine learning and data science applications
in health economics and outcomes research (HEOR) and pharmacovigilance. This fellowship provides an excellent opportunity to enhance analytical skills and advance research agendas through both formal training and extensive collaboration with leading researchers.Postdoctoral scholars will serve as research trainees to enhance and develop their research competencies. Scholars will work directly with senior Faculty such as Drs. Dana Goldman, Julie Zissimopoulos, Daniel McFadden and Darius Lakdawalla. Responsibilities include planning, designing, and conducting complex research projects under the guidance of mentors. The role may involve both independent and collaborative work.This new call aims to attract talented individuals eager to contribute to the advancement of health policy and economics through innovative machine learning and biostatistical methodologies.Key Responsibilities:Collaborate with USC faculty on cutting-edge research projects in health economics and policy.Design, develop, and estimate health economic models to study the clinical benefits and economic value of new health interventions. Analyze individual patient-level data and other sources to parameterize these models.Apply interpretable machine learning techniques to the study of health economic models and the analysis of patient-level healthcare data.Produce high-impact research papers, such as those focusing on the value of Alzheimer's disease treatments.Eligibility Criteria:We invite scholars who have recently completed a Ph.D. in a relevant discipline such as biostatistics, computer science, data science, health economics, health policy, or public policy to apply. Candidates should possess robust data science and programming skills, including Python, and have a keen interest in applying interpretable machine-learning methods. Candidates should also have experience constructing and analyzing cost-effectiveness and/or other health simulation models.Minimum Qualifications:Education: Ph.D. or equivalent doctorate within the previous five years.Experience: 0-1 year of relevant research experience.Field of Expertise: Interpretable machine learning, data science, and health economics.Preferred Candidate Profile:Strong programming skills in Python.Experience building cost-effectiveness and health simulation models.Proficiency in interpretable machine learning techniques.Demonstrated ability to publish in peer-reviewed journals.Compensation and Duration:The annual base salary range for this full-time position is $75,000 - $100,000. When extending an offer of employment, the University of Southern California considers factors such as (but not limited to) the scope and responsibilities of the position, the candidate's work experience, education/training, key skills, internal peer equity, federal, state, and local laws, contractual stipulations, grant funding, as well as external market and organizational considerations.The fellowship provides a competitive stipend and other benefits for a 12-month fixed term, which may be renewed up to a maximum of two years. Hybrid work arrangement.Application Process:Please upload CV, cover letter, writing sample, one-page statement of research interest and recent reference letter(s) as a single combined PDF file. Python code samples may be requested during the interview process.Application Deadline:Applications will be considered as they are received until the position(s) is filled.
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