Dongwon Lee Lab | Announcements

Full-time postdoctoral positions are available in Dongwon Lee’s laboratory. We study disease-associated genetic variants using computational approaches with a particular focus on transcriptional regulatory mechanisms. We have developed several machine-learning methods for the analysis of regulatory elements and regulatory variants (Lee et al., Nature Genetics 2015; Lee, Bioinformatics 2016; Lee et al., Genome Research 2018; Han et al., PNAS 2022). Projects will include the development of computational methods to model regulatory control of human disease by incorporating improved machine learning algorithms and single-cell multi-omic data (genomic, transcriptomic, and epigenomic). There will also be ample opportunity to collaborate with clinicians and wet-lab biologists to apply our methods to clinical genetic and genomic data and to validate our computational predictions in model systems.

1. The applicant should have a Ph.D. degree in computational biology, bioinformatics, bioengineering, biostatistics, computer science, or other related fields.
2. Strong programming skills in Python, R, C/C++, or equivalent are required.
3. Experience with Unix/Linux and working with large genetic and genomic data in a high-performance cluster computing environment is highly preferred.
4. Excellent written and verbal communication skills and a willingness to write grant proposals and manuscripts are necessary.

Interested candidates should send a CV including three references, a cover letter, and representative papers (up to two) to: dongwon.lee@childrens.harvard.edu

Dongwon Lee, PhD
Assistant Professor of Pediatrics, Division of Nephrology,
Boston Children’s Hospital, and Harvard Medical School
Manton Center Associate, The Manton Center for Orphan Disease Research
Associate Member, Broad Institute of MIT and Harvard

We are an equal opportunity employer and all qualified applicants will receive consideration for employment without regard to race, color, religion, sex, national origin, disability status, protected veteran status, gender identity, sexual orientation, pregnancy and pregnancy-related conditions or any other characteristic protected by law.