The Geeleher Lab is seeking outstanding candidates for fully supported postdoctoral fellowships focused on developing innovative computational and statistical approaches to inform and improve therapies for pediatric cancer and other diseases. One of the premier pediatric research institutions in the world, St. Jude Children’s Research Hospital provides exceptional resources and a supportive environment for career development.
As a postdoctoral fellow, you will interact with leaders in cancer and translational research within and outside the institution and at national/international meetings. Innovative research will be supported by the lab’s infrastructure, which includes a wet-lab component. Postdocs have considerable flexibility and freedom to develop their research programs. Learn more at geeleherlab.org.
Current research areas
Identifying targeted therapies for patients with cancer is a central focus at St. Jude, and genome and RNA sequencing of patients’ tumors is now being performed regularly as part of standard-of-care. A major goal of the Geeleher lab is to explore machine learning approaches to prioritize targetable variants and expand the scope of targeted therapeutics.
The postdoc will explore, optimize and build on emerging informatics techniques, including integrating somatic variation with transcriptomic variation and with protein-protein interaction networks. The Geeleher lab’s wet-lab component provides a platform for validation of computational predictions and discoveries. Successful completion of the project has the potential for a direct positive impact on patient care and high-impact publications.
Chemotherapeutic response is a complex trait influenced by numerous factors. Inherited genetic variants influencing gene expression (expression quantitative trait loci, or eQTLs) have been identified as major contributors. However, our recent work has shown that the degree of influence of eQTLs on gene expression in cancer is less well understood than previously thought.
The postdoc will explore how inherited genetic variation influences cancer risk, disease progression and drug response, building on methods developed in the lab to deconvolute eQTL signals from bulk tissue expression data to specific cell types. This work will aim to improve our understanding of inherited genetic variation in cancer and yield computational approaches applicable to a broad variety of complex traits and diseases.
Candidates must hold a doctoral degree (Ph.D., M.D. or equivalent). Applicants with a Ph.D. in a quantitative field (computational biology, genetics/genomics, statistics, mathematics, computer science & related fields) are encouraged to apply. Strong candidates from a primarily wet-lab or clinical background who wish to develop sophisticated quantitative skills will also be considered. Successful candidates will have a track record of scientific productivity, e.g. a first author paper, or a demonstrable contribution to a large project. Experience working in pediatric cancer is an advantage but not necessary. Fluency in English and the ability to think and work independently are essential.
Positions are available starting February 2019. The initial appointment will be for 1-2 years and can be renewed for up to a total of 5 years, depending on the candidate’s goals and qualifications.
Interested candidates, please complete the online application and email your CV and cover letter to email@example.com. Please include areas of specific interest in a brief cover letter.
About the Geeleher Lab
The lab of Dr. Paul Geeleher is in the Department of Computational Biology at St. Jude Children’s Research Hospital. Dr. Geeleher is recognized for developing innovative computational approaches and has led drug repurposing efforts, spearheaded publications in Nature, Genome Research, Genome Biology, Journal of the National Cancer Institute (JNCI) and Bioinformatics in the last five years, and is funded by the NIH. Postdoctoral fellows in the lab will benefit from access to the wealth of high-quality genomics data generated at St. Jude, state-of-art high-performance computing facilities, robust analytical pipelines, the latest laboratory technology, outstanding core facilities and scientific expertise in genomics, cancer biology, statistics, and computer science.
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