The Atkinson lab in the Department of Molecular & Human Genetics is recruiting a motivated Postdoctoral Associate to lead research projects in statistical and population genomics across diverse human populations. This postdoc will use large-scale genomic datasets to decrease disparities in genetics research across ancestry groups. They will have opportunities for driving analyses in consortium projects and gain mentorship experience via helping to train junior investigators in the group. The postdoc will have the flexibility to tailor projects to their own related areas of interest and work on a range of efforts, including:
• Elucidating the genetic architecture of complex (primarily psychiatric) traits in diverse cohorts using ancestry-informed methods for GWAS, PRS, and heritability analyses
• Extending and developing statistical and computational tools for the improved genomic study of diverse populations
• Characterizing patterns of admixture, demographic history, and evidence of natural selection for key human phenotypes in diverse understudied cohorts
Our lab is in the leadership of multiple international consortia including the Psychiatric Genomics Consortium (PTSD working group), Neuropsychiatric Genetics in African Populations study (NeuroGAP), and the Latin American Genomics Consortium, affording trainees access to a wealth of diverse large-scale genomic datasets containing a wide range of phenotypes for potential study. Baylor College of Medicine is a global leader in genetics research and provides a vibrant multidisciplinary research environment with close links to many other world-class institutions in the Texas Medical Center as well as BCM-affiliated hospitals across Houston. As a member of our team, you will be provided the opportunity for your contributions to be utilized and recognized across the vast global network of researchers in the fields of genomics and psychiatric disease research.
The successful candidate will take ownership of their project, including involvement in the design, implementation and troubleshooting of analyses, interpretation of data & results, and writing manuscripts and abstracts to report the discoveries in the forms of journal publications and conference communications.
• Analyze large genomic datasets including ancestrally diverse participants and/or modeling demographic history.
• Characterize the genetic basis of psychiatric and other complex disorders.
• Conduct analysis of large-scale datasets in a high-performance computing cluster or cloud-based system.
• Build flexible analytic pipelines and computational resources for study of diverse cohorts.
• Implement statistical genetic tests.
• Interact with and training of junior researchers from diverse backgrounds.
• Disseminate results in the form of publications and conference presentations.
- MD or Ph.D. in Basic Science, Health Science, or a related field.
- No experience required.
Candidates with backgrounds in genomics, population genetics, bioinformatics, and/or statistics would thrive in our group. Ideal candidates for this role would have a PhD in a relevant field and experience/interest in several of the following domains:
• Analyzing genomic datasets including ancestrally diverse participants and/or modeling demographic history
• Conducting analysis of large-scale datasets in a Unix system on a high-performance computing cluster or cloud-based system
• Coding experience, preferably with some background in python and/or R
• Comfort with statistical analysis, especially linear/logistic regression
• Willingness to interact with and train junior researchers from diverse backgrounds
• Strong writing and presentation skills
• Scientific creativity and the ability to work well in a team as well as independently
Strong skills in genomics and an interest in diverse populations are expected. While we study a range of phenotypes and populations, our work is centered around psychiatric traits and mixed populations, so experience in these areas is a plus.
Baylor College of Medicine is an Equal Opportunity/Affirmative Action/Equal Access Employer.