Post-Doctoral opportunity - Genomic analysis
Post-Doctoral Associate position now open in bioinformatics and genome analysis
Oklahoma Medical Research Foundation, Arthritis & Clinical Immunology Department
Job Summary/Basic Function:
Our lab is designing methods to understand what experimental genomic regions of interest (e.g., SNPs from a GWAS, ChIP-seq peaks, etc) have in common, and how polymorphic tandem repeats may be associated with phenotype. We collaborate with multiple laboratories, internally and externally, to help them interpret and understand their genomic data, as well as to better understand the relationship between genomic architecture (e.g., epigenomics) and disease onset.
We seek a Postdoctoral Associate to join our efforts to better understand the phenotypic implications of genomic alterations. This work is based on the hypothesis that there are unifying features behind sets of observed genomic changes, and the challenge is to develop algorithmic means of identifying and prioritizing them. This work has the potential to rapidly accelerate our understanding of disease risk and etiology.
The candidate will develop methods to obtain and incorporate genomic annotations and features from multiple sources, mostly public databases. They will develop methods of exploratory data analysis, such as identifying experimental genomic regions of interest that overlap with these annotations, are proximal to them, vary in terms of their magnitude, etc. The goal of the project is to advance scientific understanding of genomic organization and interpret experimental data from multiple collaborators (with many opportunities for co-authorship on projects). The candidate should have solid programming skills and demonstrable programming experience (e.g., publications where they contributed to algorithm development). Familiarity with software and methods for genomic analysis and analysis of next gen sequencing data is greatly preferred. We have access to a strong array of analytical computing resources.
Minimum Qualifications:
- Ph.D. in a quantitative discipline such as Computer Science, Bioinformatics, or in Physics/Biology with a strong quantitative background.
- Strong experience in writing computer programs in at least one widely used language (e.g., Python, C++, R, Visual Basic) is required.
Preferred Qualifications:
- Experience analyzing/processing next-generation sequencing data preferred.
- Experience with analysis of genomic sequence data is preferred.
- Machine learning and/or large scale data mining experience is a plus.
- Must demonstrate strong personal initiative and the ability to work effectively as part of a team.
Please send CV to or Contact:
Jonathan D. Wren, Ph.D.
Oklahoma Medical Research Foundation
825 N.E. 13th Street, Rm MC103
Oklahoma City, Oklahoma 73104-5005
[email protected]
Oklahoma Medical Research Foundation, Arthritis & Clinical Immunology Department
Job Summary/Basic Function:
Our lab is designing methods to understand what experimental genomic regions of interest (e.g., SNPs from a GWAS, ChIP-seq peaks, etc) have in common, and how polymorphic tandem repeats may be associated with phenotype. We collaborate with multiple laboratories, internally and externally, to help them interpret and understand their genomic data, as well as to better understand the relationship between genomic architecture (e.g., epigenomics) and disease onset.
We seek a Postdoctoral Associate to join our efforts to better understand the phenotypic implications of genomic alterations. This work is based on the hypothesis that there are unifying features behind sets of observed genomic changes, and the challenge is to develop algorithmic means of identifying and prioritizing them. This work has the potential to rapidly accelerate our understanding of disease risk and etiology.
The candidate will develop methods to obtain and incorporate genomic annotations and features from multiple sources, mostly public databases. They will develop methods of exploratory data analysis, such as identifying experimental genomic regions of interest that overlap with these annotations, are proximal to them, vary in terms of their magnitude, etc. The goal of the project is to advance scientific understanding of genomic organization and interpret experimental data from multiple collaborators (with many opportunities for co-authorship on projects). The candidate should have solid programming skills and demonstrable programming experience (e.g., publications where they contributed to algorithm development). Familiarity with software and methods for genomic analysis and analysis of next gen sequencing data is greatly preferred. We have access to a strong array of analytical computing resources.
Minimum Qualifications:
- Ph.D. in a quantitative discipline such as Computer Science, Bioinformatics, or in Physics/Biology with a strong quantitative background.
- Strong experience in writing computer programs in at least one widely used language (e.g., Python, C++, R, Visual Basic) is required.
Preferred Qualifications:
- Experience analyzing/processing next-generation sequencing data preferred.
- Experience with analysis of genomic sequence data is preferred.
- Machine learning and/or large scale data mining experience is a plus.
- Must demonstrate strong personal initiative and the ability to work effectively as part of a team.
Please send CV to or Contact:
Jonathan D. Wren, Ph.D.
Oklahoma Medical Research Foundation
825 N.E. 13th Street, Rm MC103
Oklahoma City, Oklahoma 73104-5005
[email protected]