Postdoctoral Researcher (Bioinformatics)
The Penn Medicine Center for Ophthalmic Genetics in Complex Diseases is seeking a postdoctoral researcher with a focus on bioinformatics. The mission of the Center is to elucidate the genetics of diseases that over-affect African ancestry populations. Currently, a large focus of our lab is on glaucoma genetics. This candidate would help to complete the aims of the NIH-funded Primary Open-Angle African American Glaucoma Genetics (POAAGG) study, which has enrolled over 10,200 African ancestry individuals from Philadelphia. We have GWAS data on 7765 individuals, whole-exomes on 8500 individuals, and whole-genomes on 100 individuals. This candidate would lead bioinformatics analyses on this data, under the guidance of the PI and research directors, with the opportunity to expand into other diseases in the future. The successful candidate will be dedicated and motivated, have strong creative thinking skills, and be a driver of their research. This is an exciting opportunity to work with a group of experts in computational genomics and functional genomics with direct clinical applications, and to improve algorithms and develop software tools to better understand minority genetics.
· Perform post-GWAS analyses on samples collected from the POAAGG study, described above.
· Construct a polygenic risk model for glaucoma in African ancestry individuals.
· Conduct a meta-analysis with other glaucoma cohorts to discover novel associations.
· Analyze whole-exome data to study the contribution of rare variants to glaucoma.
· Perform other bioinformatic analyses as needed.
· Interpret resulting data and submit findings in peer-reviewed journals and present at national and international meetings.
· Provide supervision and guidance to students as needed.
· PhD in Computer Science, Statistics, Bioinformatics, Genetics, or a related discipline with a strong understanding of biology.
· Strong interest in human genetics and common complex diseases.
· Strong computational/statistical skills with experience in handling large genomic datasets, population genetics analyses, and/or quantitative analyses of complex traits.
· Good understanding of deep learning algorithms, strong programming skills, and experience in genomics algorithm development and/or machine learning.