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Postdoctoral Researcher - Mcdermott Center HG&D - Seplyarskiy Lab Req Position
Job in
Dallas, Dallas County, Texas, 75215, USA
Listed on 2026-06-02
Listing for:
UT Southwestern Medical Center
Apprenticeship/Internship
position Listed on 2026-06-02
Job specializations:
-
Research/Development
Research Scientist, Data Scientist
Job Description & How to Apply Below
Description
Postdoctoral Researcher in Mutagenesis, Population and Statistical Genetics
A postdoctoral training opportunity is now available in the Seplyarskiy Lab in the McDermott Center for Human Growth and Development at UT Southwestern Medical Center are currently accepting applications for a postdoctoral fellowship in mutagenesis, statistical genomics, and computational biology.
Research directions
- Mutagenesis: evolution of mutational mechanisms across the tree of life; somatic mutagenesis and clonal dynamics; reconstruction of early developmental lineages from mosaic mutations.
- Population genetics: quantifying recurrence and number of mutational origins in large cohorts; discovery of strongly selected sites and constraint from recurrence-aware models.
- Statistical genetics: partitioning heritability and enrichment in DNA-repair and mutagenesis pathways (including cancer-relevant contexts); development of mutation rate model
- Close mentorship in mutagenesis, population genetics, and statistical genetics
- Active joint journal clubs with external groups (Ziyue Gao - UPenn, Evan Koch - Yale), collaborative community at UTSW's McDermott Center.
- Access to large datasets (e.g., biobanks, gnom
AD-class resources) and compute.
- Formulate and test new quantitative models of mutation, selection, and clonal evolution.
- Develop methodstailored to large-scale genomic datasets.
- Lead analyses, interpret results and drive manuscripts to completion.
- Collaborate on related work across the lab's projects.
• Ph.D. (or equivalent, or soon to be completed) in Statistics, Biostatistics, Computer Science, Population/Statistical Genetics, Bioinformatics/Computational Biology
• Proficiency in R and/or Python/ or other languages
• Plus factors: experience with method development, exposure to population-genetic theory (selection, demography, coalescent/ARG), mutational-process modeling, scalable data engineering, cloud/HPC, or ancient DNA.
Application Instructions
Interested individuals should send a CV, cover letter briefly describing previous research experience, and a summary of current research interests.
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