The fellow will leverage extensive omics data and specimens from the NIH Longitudinal Study of Vaginal Flora, a cohort of 3,620 women followed quarterly, with more than 13,000 archived cervicovaginal specimens and detailed longitudinal clinical data, including standardized symptom assessments and pelvic examinations.
The project will examine:
- How often asymptomatic, untreated MG progresses to cervicitis, pelvic inflammatory disease, and other clinical syndromes
- Whether MG is independently associated with these outcomes after accounting for co-infections
- How the vaginal microbiome and immune response influence progression to symptomatic disease versus spontaneous clearance
This position offers substantial opportunities to lead first-author publications, present research at national and international scientific conferences, contribute to grant development, and build an independent research program at the intersection of epidemiology, infectious diseases, microbiome science, and women's health.
Responsibilities
- Conduct epidemiologic and statistical analyses of longitudinal clinical and high-dimensional microbiome data
- Apply and develop methods for multi-omic data integration, including metagenomic and immune-profiling data
- Interpret findings within epidemiologic and biological frameworks
- Lead first-author manuscripts and co-author publications in high-impact peer-reviewed journals
- Present research at national and international scientific meetings
- Collaborate closely with epidemiologists, statisticians, bioinformaticians, and laboratory scientists
- Contribute to study design, analytic plans, and grant development
Qualifications
- PhD, ScD, or equivalent doctoral degree in epidemiology, biostatistics, bioinformatics, microbiology, or a related field
- Strong quantitative and statistical skills, with proficiency in R or Python
- Experience analyzing longitudinal, infectious disease, clinical, or high-dimensional data
- Demonstrated record of peer-reviewed publications
- Strong scientific writing skills and the ability to translate complex analyses into clear scientific narratives
- Interest in microbiome science and women's health
- Experience with microbiome or multi-omic data analysis, causal inference methods, or infectious disease epidemiology is preferred but not required
Research and Training Environment
The fellow will join a collaborative, intellectually rigorous, and mission-driven research environment that brings together expertise in women's health, epidemiology, biostatistics, genomics, bioinformatics, microbiology, and immunology. The position provides access to deeply characterized longitudinal cohorts, curated biospecimen repositories, and state-of-the-art genomic and computational infrastructure. Through mentorship, grant writing, and participation in future observational and interventional studies, the fellow will receive strong support in developing an independent research career.
Application
Interested applicants should submit:
- Curriculum vitae
- A brief statement of research interests and relevant experience
- Contact information for three references
Applications will be reviewed on a rolling basis until the position is filled.
