A Postdoctoral Associate position is available immediately in the Center for Translational Pain Medicine at Duke University, Department of Anesthesiology, to develop, optimize and validate genomic predictive models (polygenic risk scores) for clinical outcomes in patients with chronic pain. The successful candidate will work in an interdisciplinary group of geneticists, biostatisticians, epidemiologists, and clinical scientists. S/he will develop and extend computational approaches to predict pain outcomes using high-dimensional genomic data, and develop and validate tools for personalized pain treatment strategies.
Requirements:
- PhD or equivalent in Bioinformatics, Statistical Genetics, Statistics, Genetics, Computational Biology, Computer Science, Biomedical Engineering or related field.
- Computational pipeline development for GWAS and/or sequencing data
- Proficiency in R (or Python)
- Knowledge of statistical methods
- High productivity demonstrated by publications, presentations, or contributions to bioinformatics software projects.
Desirable:
- Applying machine learning methods to genomic data
- Predictive modeling using modern approaches (regularized regression, neural networks, random forest etc)
- Working knowledge of big data and distributed computing tools
The successful candidate should also have a demonstrated ability for independent and critical thinking, excellent communication and teamwork skills, and enthusiasm for learning new things.
Email CV, cover letter and a list of three references to andrey dot bortsov at duke dot edu.
