One postdoctoral position is available immediately in Dr. Zhongming Zhao's Bioinformatics and Systems Biology Laboratory (BSBL, http://bioinfo.mc.vanderbilt.edu/) at Vanderbilt University Medical Center. The successful candidate is expected to join an established bioinformatics team, which currently comprises 14 members including six postdocs in bioinformatics, four bioinformatics engineers, several students, and one program coordinator. The ongoing projects in our group use the data generated from platforms such as microarray gene expression, GWAS, microRNA, CNVs, chip-sequencing, RNA-seq and 454 sequences to study cancer, neuropsychiatric disorders, or other complex diseases using bioinformatics and systems biology approaches. Integrative genomics approaches are often applied. The fund is available to support this position for up to three years. The candidate will have the opportunity to access many high throughput datasets and to interact with numerous investigators in multiple fields, especially through Vanderbilt-Ingram Cancer Center.

Vanderbilt's Department of Biomedical Informatics is the largest academic department of biomedical informatics in the country, with more than 65 faculty members, a graduate training program, and a portfolio of research and development projects that spans from computational biology and bioinformatics applied to the understanding of biological molecules, through advanced clinical information systems that care for hundreds of thousands of patients at Vanderbilt, to regional health information projects that span many states. More information about the department can be found at http://dbmi.mc.vanderbilt.edu/ .

The qualified candidates should be highly motivated in research and have a Ph.D. in bioinformatics, computational biology, molecular biology, or related when the job starts. Candidates who are interested in non-tenure track faculty position in our group are particularly encouraged to apply since such position(s) are available. The successful candidate should have some experience in analyzing high-throughput genomic data and proved skills in at least one programming language (Perl, Java, or C/C++). Good understanding of molecular biology and familiarity with biostatistics are desirable.