[Hiring] Research Postdoctoral Fellow @Geisinger

Role Description

The Research Postdoctoral Fellow will join an interdisciplinary research team focused on precision health, population genomic screening, risk-stratified disease prevention, health economics, and real-world evidence generation. The fellow will contribute to federally funded and industry-sponsored research projects that evaluate the clinical, economic, and implementation impact of precision disease screening strategies using large-scale electronic health record (EHR), claims, machine learning and artificial intelligence methods, and cost-effectiveness modeling. This position offers opportunities for growth and development in health economics, decision-analytic modeling, ML and AI methods, and population health research while collaborating with investigators across multiple clinical and research disciplines.

• Conducts research related to specific project or initiative.
• Gathers, summarizes, records and interprets data obtained from research projects and initiatives.
• Plans subsequent work with review and approval of principal scientist and investigator.
• Develops research protocols.
• May instruct others in area of expertise.
• May present research results at internal and external scientific venues.
• Interprets and follows policies and guidelines to define procedures and meet goals and deadlines.

Work is typically performed in an office environment. Accountable for satisfying all job specific obligations and complying with all organization policies and procedures. The specific statements in this profile are not intended to be all-inclusive. They represent typical elements considered necessary to successfully perform the job.

Qualifications

• PhD, MD, DrPH, ScD, or equivalent doctoral degree in Health Economics, Health Services Research, Epidemiology, Biostatistics, Public Health, Data Science, Biomedical Informatics, Computer Science, Economics, or a related field.
• Strong quantitative and statistical analytical skills.
• Experience with statistical programming (R, SAS, Python, STATA, or similar).
• Demonstrated excellent scientific writing ability.
• Excellent communication and teamwork skills.
• Ability to work independently and collaboratively in a multidisciplinary environment.

Requirements

• Experience or interest in conducting health economic evaluations and decision-analytic modeling.
• Experience with machine learning and AI engineering, e.g. generative AI applications, agentic AI systems.
• Experience analyzing EHR, claims, registry, or other large health dataset.
• Interest in precision medicine, or risk-stratified disease screening and prevention.
• Record of peer-reviewed publications.
• Experience supporting funded research projects and grant applications.

Benefits

• Mentorship and career development opportunities.
• Participation in NIH-funded and industry-sponsored research.
• Experience with large-scale EHR, claims, and genomic datasets.
• Opportunities for scientific leadership, publication, and grant development.
• Collaborative environment with investigators across clinical, genomic, and population health disciplines.