AI/ML Postdoctoral Research Position at the NIH

underlying cell-type–specific regulatory signals and to pinpoint disease-causal noncoding mutations.

Applicants should hold a PhD in Computational Biology, AI/ML, Computer Science, Population Genetics, Bioinformatics, or a related field, and have fewer than five years of postdoctoral experience. Strong programming skills and experience analyzing genomic data are highly desirable.

Selected recent publications:

• D. Huang et al., Silencer variants are key drivers of gene up-regulation in Alzheimer's disease, Science Advances, 2026
• D. Huang et al., Super-silencers are crucial for development and carcinogenesis in B cells, Nature Communications, 2025
• D. Huang et al., The contribution of silencer variants to human diseases, Genome Biology, 2024
• S. Hudaiberdiev et al., Modeling islet enhancers using deep learning identifies candidate causal variants at loci associated with T2D and glycemic traits, PNAS, 2023
• S. Li et al., De novo human brain enhancers created by single-nucleotide mutations, Science Advances, 2023

This is a full-time postdoctoral fellow position. The initial appointment will be for one year, and is renewable on a yearly basis, with extensions up to 5 years total. The NIH offers a competitive salary (based on postdoctoral experience, see stipend tables: https://www.training.nih.gov/stipends/) and comprehensive health insurance. The NIH is dedicated to the continued education and career development of all its research staff. Candidates are subject to a background investigation.

If interested, please email your CV and the names of three references to Dr. Ivan Ovcharenko at ovcharen@nih.gov.