CDC Prevention Effectiveness Fellowship 2026: Two-Year Paid Postdoc in Public Health Decision Science (GS-12)

If you want to move from crunching numbers in a quiet corner of academia to shaping public health policy at the Centers for Disease Control and Prevention, the Steven M. Teutsch Prevention Effectiveness (PE) Fellowship is one of the most direct routes. This is a two-year, salaried postdoctoral fellowship that places early-career quantitative researchers into real-world decision science work inside CDC. You’ll be paid at the federal General Schedule (GS) 12, step 3 level and get the same benefits CDC employees receive — medical coverage, leave, retirement contributions — while doing projects that influence vaccine policy, cost-effectiveness analyses, outbreak response modeling, and more.

Think of it like an apprenticeship where the tools are advanced statistical models, cost-effectiveness frameworks, and public health program data, and the workshop is CDC’s decision science community. The program typically accepts about 20 fellows annually (roughly 10 on the Traditional Track and 10 on the Analytics and Modeling Track), most of whom are placed at CDC headquarters in Atlanta. Some placements may be with state or local public health agencies. If you have technical chops and care about practical impact, this fellowship is worth your attention — but competition is stiff and the application needs to be precise.

At a Glance

Why This Fellowship Matters

There are many postdocs you can take after your PhD. Most keep you in the ivory tower, doing incremental work that may take years to reach practitioners. The PE Fellowship puts you at the interface between rigorous methods and public health decisions that happen fast. You’ll work on analyses that can inform guidelines, budgets, outbreak responses, or program design. That kind of immediate relevance builds a different résumé: one that says you can translate technical work into decisions and policy.

Beyond the headline work, the fellowship gives access to a multi-disciplinary decision science community inside CDC. That means mentorship from economists, epidemiologists, modelers, and program evaluators who are actively consulting with policy teams. For someone who wants a career at the crossroads of method and practice — academic or applied — this fellowship accelerates learning and offers a network that lasts longer than two years.

Finally, it’s a paid federal role. That matters. You won’t be dependent on temporary stipends or precarious funding, and you’ll be eligible for federal employee benefits. There’s also a pathway to a salary review after year one based on performance. Financial stability combined with influential work: that’s a rare combo for early-career researchers.

What This Opportunity Offers

The PE Fellowship provides structured professional development and hands-on project assignments. Fellows typically engage in one or more of the following types of work: cost-effectiveness analyses of prevention programs, economic modeling for vaccine policy, infectious disease transmission models, decision-analytic frameworks for public health interventions, and program evaluation using administrative or survey data. You’ll learn to shape analyses so they answer the practical questions decision makers ask — not just the academic ones.

Mentoring is built into the program. Each fellow is embedded in a team where senior analysts and CDC program staff provide guidance. That mentorship translates into better research products and a clearer sense of how to package findings for policy audiences. You’ll also benefit from the collegial environment at CDC: seminars, methodological working groups, and cross-disciplinary collaborations are part of the day-to-day.

The fellowship pays at GS-12 step 3 and includes standard federal benefits. There is potential for a salary adjustment after the first year if management recommends it. Note that fellows are responsible for their own relocation expenses; CDC does not provide moving allowances for this role. Placements are usually at CDC headquarters in Atlanta, but some positions may be located in state or local public health agencies when program needs require it.

Who Should Apply

The program is explicitly aimed at recent PhD graduates and equivalent degree holders who have strong quantitative training and a clear interest in applied public health research. There are two tracks and each has its own flavor.

Traditional Track: This route typically suits candidates with a PhD in fields like economics, agricultural economics, health services research, public health, or other quantitative social sciences. If your work uses economic evaluation, decision analysis, or health services data to answer policy questions, the Traditional Track is a natural home. Examples: an economist who has done cost-effectiveness work on tobacco cessation programs, or a health services researcher who evaluated interventions in health systems using quasi-experimental designs.

Analytics and Modeling Track: This track favors candidates with backgrounds in epidemiology, infectious disease modeling, disease ecology, applied mathematics, operations research, data science, or related biological or analytic disciplines. If you build transmission models, run stochastic simulations, or write code to analyze large surveillance datasets, you’ll fit here. Examples include a modeler who worked on COVID-19 transmission scenarios or a data scientist who developed pipelines for cleaning and analyzing state surveillance data.

Citizenship and work authorization rules are important. US citizens and permanent residents are eligible. F1 visa holders can be considered only if they have OPT with EAD that will cover the entire first year of the fellowship and if they meet STEM OPT eligibility requirements. Candidates with other immigration statuses may be contacted if they progress, but initial eligibility centers on the groups above.

If you’re an academic who wants to keep one foot in method development and the other in policy impact, this program is tailored to you. If you want to remain strictly bench or purely theoretical, you might find the pace and priorities here frustrating.

Insider Tips for a Winning Application

Applying to PE Fellowship is not a box-ticking exercise. Reviewers are looking for evidence that you understand both rigorous methods and applied public health questions. Here are practical, specific tactics that give your application muscle.

1. Tell a coherent story across documents. Your CV, personal statement, and writing sample should all point to the same competencies and interests. If your CV shows modeling skills and your statement emphasizes economic evaluation, explain how those abilities connect. Make the thread visible.

2. Show methodological depth and practical experience. Don’t just list MATLAB or R on your CV. Describe a project where you used those tools to answer a real question: the data you used, the obstacles you overcame, and the policy-relevant conclusion. Short, concrete examples beat vague claims.

3. Be explicit about your role in collaborative projects. Reviewers want to know what you actually did. If you were part of a team that produced a high-profile analysis, clarify whether you led the statistical work, developed the model structure, or managed data pipelines. That distinction matters.

4. Provide a polished writing sample that highlights applied work. Prefer a short manuscript, brief technical report, or policy memo over a dense theoretical thesis chapter. Choose a sample that demonstrates your ability to explain results to non-technical audiences.

5. Get strategic recommendation letters. Ask referees who can speak to your technical abilities and to your potential for applied work in public health. A letter from an advisor that says “excellent theoretician” is fine, but pair it with a letter from a practitioner or collaborator who can vouch for your applied instincts.

6. Build a small portfolio if possible. A GitHub repo with cleaned code, a short technical appendix, or a public dashboard demonstrates reproducible work habits. Make sure everything is tidy and well-documented — sloppy code will hurt more than help.

7. Prepare for the interview like it’s a consulting case. You’ll be asked technical questions and situational ones. Practice explaining your previous projects in five minutes, then in two minutes, and then as a 30-second elevator pitch. Be ready to walk a non-specialist through the logic of a model or an economic evaluation.

8. Address potential weaknesses proactively. If you lack formal experience in a key method, show how you made up for it with recent coursework, online certificates, or collaborators who fill that gap. Don’t ignore gaps — explain them.

These tips aren’t cosmetic. The reviewers are experienced analysts who can see false polish from a mile away. Authenticity — backed by tangible outputs — wins.

Application Timeline (Work Backwards from January 9, 2026)

Start early. Competitive candidates begin preparing three months before the deadline.

• 10–12 weeks before deadline: Decide which track fits you. Draft a one-page outline of your application narrative and ask two people for early feedback.
• 8–10 weeks before deadline: Prepare your CV and select a writing sample. Contact potential letter writers and give them at least four weeks’ notice. Share your one-page outline so their letters align with your story.
• 6–8 weeks before deadline: Draft the personal statement. This is where you explain why CDC, why prevention effectiveness, and what you will bring. Get feedback from a mentor who understands applied public health.
• 4–6 weeks before deadline: Finalize letters of recommendation and the writing sample. Begin polishing attachments and ensure file formats meet application rules.
• 2 weeks before deadline: Do a full application review. Check every field. Make sure your OPT EAD (if applicable) covers the first year and that your letter writers submitted their letters.
• 48–72 hours before deadline: Submit. Federal portals can be finicky. Submit early to allow time for technical problems and last-minute edits.

Block time in your calendar for review and revisions. Rushed applications are obvious.

Required Materials and How to Prepare Them

The program evaluates academic preparation, recommendations, research and work experience, publication record or publication potential, methodological and data skills, and a personal statement. Here’s how to assemble materials that show those elements.

• Personal Statement: Use this to explain your motivation, relevant training, and what you want to accomplish during the fellowship. Write in plain language. Include a short paragraph about a project idea you’d be excited to work on — specific but flexible.
• CV: Focus on training, methods, and outputs. Include technical skills, relevant coursework, and reproducible research artifacts (links to code or data if public).
• Writing Sample: Pick a concise, applied piece. Policy briefs, technical reports, or short manuscripts work best. If your thesis is the only option, provide a 2–5 page executive summary that highlights contributions and implications.
• Letters of Recommendation: At least two, ideally three. One should be from your doctoral advisor or principal investigator, assessing your technical skills and independence. Another should be from someone who can speak to your collaborative ability and applied problem-solving.
• Proof of Degree: Official documentation that your PhD or equivalent will be completed prior to the fellowship start date (for Traditional Track).
• Work Authorization Documents: For F1 applicants, provide OPT/EAD documentation showing coverage for the first year and STEM eligibility.
• Optional: Supplemental materials such as a short project proposal or a GitHub link that demonstrates code quality and reproducibility.

Prepare these early. Ask letter writers to focus on specific examples: times you solved a problem, led a component of a study, or communicated complex results to stakeholders.

What Makes an Application Stand Out

Reviewers evaluate both technical mastery and the ability to produce policy-relevant outputs. Applications that succeed usually do three things well.

First, they show technical competence with evidence: publications, code, or presentations that demonstrate you can do the work without heavy ramp-up time. Second, they show applied judgment: candidates who articulate how their analyses would inform a policy question (budget trade-offs, prioritization decisions, or implementation choices) are more compelling. Third, they demonstrate teamwork and communication skills. At CDC you’ll be working with program staff who are not methodologists. If you can explain results clearly and persuasively, your work will be used.

A strong application aligns prior experience with the kinds of projects CDC runs. For example: an applicant who used decision analytic models to compare vaccination strategies, and who can point to a short memo they wrote for a local health department, shows both relevance and impact. Quantify outcomes where possible: “my model reduced expected hospitalizations by X in scenario analysis” or “my evaluation helped inform a policy change adopted by Y county.”

Finally, reviewers value realism. Propose modest, achievable objectives and explain limitations frankly. A candidate who overpromises on scope looks less credible than one who lays out a focused plan and a sensible plan B.

Common Mistakes to Avoid

Even excellent applicants stumble on avoidable errors. Here are pitfalls and how to fix them.

1. Vagueness about your role. Don’t write “contributed to modeling work.” Say exactly what you built, coded, or analyzed. Clear responsibility signals leadership and competence.

2. Submitting an overly academic writing sample. Dense theoretical chapters are hard to parse. Choose applied work that demonstrates clarity and decision focus.

3. Ignoring the practical audience. If your statement reads like a grant proposal with only academic metrics, add paragraphs showing how results would inform policy or program choices.

4. Poor letter coordination. If all letters say the same thing, reviewers learn nothing new. Ask each letter writer to emphasize a different dimension (technical skill, collaboration, leadership).

5. Missing documentation for immigration eligibility. If you’re an F1 applicant, verify OPT EAD dates early. Missing or expired authorization can disqualify you late in the process.

6. Rushing the narrative. A personal statement that is generic will be passed over. Spend time making a crisp case for fit.

Fix these by checking each application component against explicit reviewer criteria: methods, applied experience, publications/potential, and communication. If any piece is weak, address it directly rather than hoping reviewers won’t notice.

Frequently Asked Questions

Q: Do I need a PhD to apply? A: For the Traditional Track, applicants must hold a PhD or equivalent before the fellowship starts. The Analytics and Modeling Track typically expects strong quantitative graduate-level training; a PhD is preferred but check specific announcements for exceptions. If you’re unsure, contact the program office early.

Q: Can international applicants apply? A: US citizens and permanent residents are eligible. F1 visa holders may apply only if they have OPT with an EAD valid for the entire first year of the fellowship and meet STEM OPT eligibility. Other visa categories are evaluated on a case-by-case basis if the candidate advances, but don’t assume sponsorship will be available.

Q: Is relocation covered? A: No. Fellows are responsible for relocation costs. Factor that into your decision if moving to Atlanta or another placement is necessary.

Q: What does GS-12, step 3 mean in practice? A: It refers to a federal pay grade. It provides a stable early-career salary with federal benefits. Exact take-home pay varies by locality pay adjustments (Atlanta vs. other duty stations).

Q: Will I get a permanent CDC job after the fellowship? A: There’s no automatic conversion, but fellows often compete successfully for CDC positions or other public health roles after completing the program. The fellowship provides practical experience and a network that makes job transitions smoother.

Q: How competitive is the fellowship? A: The program accepts around 20 fellows annually. Expect strong competition from candidates with excellent methodological training and applied experience. Quality of fit and clarity of applied orientation often tip decisions.

How to Apply / Get Started

Ready to apply? Start by reading the official program page carefully and confirming eligibility. Then, follow this checklist:

1. Confirm your track (Traditional or Analytics and Modeling).
2. Contact potential recommenders and share your draft personal statement and CV so their letters are aligned.
3. Prepare a concise writing sample that highlights applied work.
4. Verify immigration/work authorization documents if you’re an F1 visa holder.
5. Complete the online application and submit well before January 9, 2026 to avoid last-minute portal issues.

Ready to apply? Visit the official opportunity page for full details and the application portal: https://cdc-efms.powerappsportals.us/programs/details/start/?appFormId=38f060ff-a673-f011-bec2-001dd804034b

If you have specific questions about eligibility or the application materials, contact the program office listed on the CDC page. They’re usually responsive and can clarify eligibility nuances early so you don’t waste time on an application that won’t pass initial screening.

This fellowship is one of those rare chances to do technically demanding work that gets read by people who make policy. If you’re drawn to applied decision science and can write, code, and explain — start your application now. January 9, 2026 will arrive sooner than you think.