Research Fellowship

Postdoctoral Research Fellowship in Epidemiology

We are inviting applications for a Postdoctoral Research Fellowship in molecular/genetic epidemiology, statistical genetics or related fields with an interest in human cancer and complex traits. Our research focuses on molecular/genetic epidemiology with special emphasis on the application of emerging genetic and genomic tools on human complex disease and traits, including breast cancer, reproductive aging, sex hormones, and obesity. The successful candidate will have the opportunity to work with a large portfolio of data collections with genome-wide genotyping, methylation, and RNA-seq data to develop their own research projects, and to participate in large-scale international collaborations. Ongoing projects include genome-wide association studies (GWAS), epigenetic-wide association studies (EWAS), expression quantitative trait loci (eQTLs) analysis, and mRNA-lncRNA co-expression analysis. The candidate will also help develop and implement statistical/computational methods for problems arising from genetic association studies, including, but not limited to, gene-based association analysis, gene-gene, gene-environmental interactions, pathway- and genetic network-based analysis, disease risk prediction using genetic marker data, association analysis for admixed populations, analysis of copy number variations. Projects can be tailored to suit the candidate’s research interest and expertise. We offer an excellent team-oriented research environment and opportunities for career advancement.

The ideal candidate has a PhD or equivalent doctorate, a strong background in genetic epidemiology, epidemiology, statistical genetics, bioinformatics, computational biology or a related discipline and has demonstrated scientific productivity. Applicants should have a strong computational background, expertise with statistical genetic/bioinformatic software packages applied to large genomic data sets. Ability to work within a UNIX or LINIX OS and standard statistical software list R, SAS, S-Plus or SPSS is required (preferably in C/C++, PERL). S/he will be familiar with approaches to integrate biological information from a wide-range of (publicly available) data resources. Research experience in regulatory genomics and/or the genetics of cancer and reproductive traits is a strong advantage. Skills in molecular biology techniques in laboratory such as genomic DNA /RNA preparation from biosamples, PCR, cloning, methylation experiments, gene functional analysis are preferable but not required.

To apply, please send CV, cover letter, and list of three references to: 
Chunyan He, Sc.D.
chunhe@iu.edu 
Department of Epidemiology
IU Richard M. Fairbanks School of Public Health
980 West Walnut Street, R3-C241
Indianapolis, IN 46202