Research Postdoctoral Fellow

Geisinger; United States; Remote; USD 65,000 - 85,000; Full time

Job summary

Geisinger is seeking a Research Postdoctoral Fellow to join an interdisciplinary team focused on precision health, population genomic screening, risk-stratified disease prevention, health economics, and real-world evidence generation.

The fellowship will contribute to federally funded and industry-sponsored projects evaluating clinical, economic, and implementation impact using large-scale EHR data, claims, ML/AI methods, and cost-effectiveness modeling, with growth opportunities across multiple

Qualifications

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

Responsibilities

• Conduct research on specific project or initiative.
• Analyze large healthcare datasets, including electronic health records, claims.
• Develop and optimize machine learning models, generative AI applications, and agentic AI systems.
• Publish findings in peer-reviewed scientific journals.
• Present research at national and international conferences.
• Assist with grant development, manuscript preparation, and scientific reporting.

Skills

Quantitative analysis

Statistical programming

Scientific writing

Communication

Teamwork

Independent work

Education

Doctoral degree

Tools

R

SAS

Python

STATA

Job description

Location:

Work from home (Pennsylvania)

Shift:

Days (United States of America)

Scheduled Weekly Hours:

40

Worker Type:

Fixed Term (Fixed Term)

Exemption Status:

Yes

Job Summary:

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.

Job Duties:

• 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 follow 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.

Position Details:

Additional Responsibilities

• Conduct independent and collaborative research projects.
• Analyze large healthcare datasets, including electronic health records, claims.
• Perform statistical analyses.
• Develop and optimize machine learning models, generative AI applications, and agentic AI systems.
• Perform health economic analyses.
• Publish findings in peer-reviewed scientific journals.
• Present research at national and international conferences.
• Assist with grant development, manuscript preparation, and scientific reporting.
• Collaborate with clinicians, scientists, data analysts, and external research partners.
• Participate in mentoring students and research staff as appropriate.

Minimum 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.

Preferred Qualifications & Skills:

• 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.