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Description

The Leslie lab in the Department of Human Genetics at Emory University School of Medicine, in Atlanta, Georgia, is looking for self-motivated, creative, and enthusiastic postdoctoral fellows to join our team. Research in the Leslie Lab focuses on understanding the etiology of structural birth defects including orofacial clefts and heart defects in Down Syndrome. We use genetic association methods, and whole exome/genome sequencing to identify novel genetic risk factors and to understand fundamental questions of phenotypic heterogeneity, penetrance, and variable expressivity.

Available projects address different aspects of the genetic architecture of these birth defects including gene discovery in Mendelian syndromes with unknown etiology, analysis of de novo and rare coding and noncoding variants, and identifying genetic modifier variants that predispose for specific phenotypes. See the Leslie Lab website (theleslielab.org) and recent published work for more information about our group and our research.

The Leslie Lab is part of the Center for Computational and Quantitative Genetics, made up of investigators with diverse research interests including methods development, population genetics, epigenetics, and human genetics. The successful candidate will have numerous opportunities to collaborate with these groups and develop additional projects.

Interested applicants should submit a cover letter detailing previous research and interest in the lab, CV, and names and contact information for three academic references.

Preferred Qualifications:Candidates should hold a Ph.D. or equivalent doctoral degree in genetics, genomics, genetic epidemiology, or a related field. Candidates with a Ph.D. in bioinformatics/quantitative sciences with substantial knowledge of topics in genetics, as well as candidates with a Ph.D. in biostatistics that have experience and interest in applied research are also encouraged to apply.

Experience with exome or genome sequencing, GWAS, or other genetic analyses, coding experience in R or python and command-line or AWS interfaces, and software tools for genetic analyses (e.g. PLINK) are preferred. The successful candidate will have strong scientific writing ability and oral communication skills.

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