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# Research Scientist (Epidemiology, Surveillance, Data & AI) in Bethesda

- **Company:** Energy Jobline
- **Location:** Bethesda, MD, United States
- **Contract:** Permanent contract
- **Skills:** Artificial Intelligence, Programming Tools, R (Programming Language), Python (Programming Language), Machine Learning, Software Tools, SAS (Software), Machine Learning Operations
- **Published:** September 4, 2026
- **Apply:** https://www.energyjobline.com/job/research-scientist-epidemiology-surveillance-data-ai-bethesda-31431700

## About the Role

* Advanced experience in epidemiology, public health, biostatistics, data science, computational epidemiology, or a closely related research field.
 * Demonstrated experience analyzing epidemiologic, disease-surveillance, population-health, or comparable health datasets.
 * Strong quantitative research skills and experience selecting or developing appropriate analytical methodologies.
 * Experience with statistical/programming tools such as R, Python, SAS, or comparable platforms.
 * For the Data & AI-focused opening: hands-on experience developing, adapting, validating, or applying AI/ML models to epidemiologic or health data is strongly .
 * For the Implementation & Services-focused opening: experience with surveillance methods, data-quality assessment, reproducible research, research repositories, or scientific tool evaluation is strongly .
 * Experience preparing scientific reports, manuscripts, publications, peer reviews, or conference presentations.
 * Ability to communicate complex technical findings clearly to scientific and interdisciplinary stakeholders.

## Description

* Plan and conduct epidemiologic research involving disease-surveillance and other public-health data.
 * Analyze, structure, clean, and evaluate large, complex, multi-source, and/or real-time surveillance datasets.
 * Assess data quality, completeness, representativeness, assumptions, and limitations that may affect research findings or model validity.
 * Develop, apply, evaluate, or improve analytical methods and AI/ML approaches for epidemiologic and surveillance research.
 * Evaluate scientific and AI/ML tools for analytic soundness, reproducibility, appropriate use, and limitations.
 * Provide technical guidance to NIH/FIC scientists and investigators on epidemiologic methods, surveillance analytics, data quality, and/or AI/ML.
 * Support investigators seeking to use, adapt, replicate, or contribute research tools and code to scientific repositories.
 * Prepare research papers, reports, presentations, and peer reviews; present findings to scientific and professional audiences.
 * Collaborate with government, academic, industry, and scientific stakeholders.


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