Postdoctoral Fellow in Statistical and Computational Genomics
Postdoctoral Fellow in Statistical and Computational Genomics, Houston, Texas
A position at the University of Texas Health Science Center at Houston is available for a Postdoctoral fellow in Statistical and Computational Genomics. The position will provide opportunities for a talented individual interested in working with large-scale genomic data in a collaborative research setting of international studies on cerebrovascular disease and dementia. The postdoctoral position will be supported by NIH grants that seek to identify the genetic and epigenetic determinants of cerebrovascular disease and dementia. The project will focus on utilizing whole genome sequence and genome-wide genotype data and DNA methylation array data on large epidemiologic cohort samples to identify biomarkers influencing risk of disease. As part of the Cohorts for Heart and Aging Research in Genomic Epidemiology (CHARGE) consortium, we are performing integrative analysis of functional omics data, whole genome sequence, and clinical data in population-based cohorts.
The successful candidate will be primarily responsible for: (1) computational analyses of whole-genome/exome sequencing datasets and genome-wide SNP array; (2) computational analyses of DNA methylation array data and their integration with genetic data, with the aim to identify novel mechanisms in neurological diseases. (3) Integrative analyses of omics data. The successful candidate will have the opportunity to lead several projects within the lab and develop active collaborations with other labs and universities in the US and Europe.
The candidate should have completed a PhD in Statistical Genetics, Computational Biology, Population Genetics/Genomics, Computer Science, or a related discipline, and have experience in the field of complex disease research. The ideal candidate would have expertise in genetics and statistical methods for genome data analysis. Experience with large-scale biological datasets, next-generation sequencing and epigenetic data is advantageous. Strong programming skills in the R language on a Linux environment is required. The position requires excellent organizational, communication, and problem-solving skills, and the ability to work, both independently and as part of a multi-disciplinary team.
Interested applicants should forward a CV and a statement of qualifications and research interests for this position, as well as the names and contact information for three professional references to:
Myriam Fornage, PhD
Professor of Molecular Medicine and Human Genetics
Laurence and Johanna Favrot Distinguished Professor
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