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