• [Photo] Xingyi Guo May 19, 2017

    BACKGROUND

    A Postdoctoral Research Associate position is available in the Division of Epidemiology, Department of Medicine, at Vanderbilt University Medical Center. Our current research concentrates on population-based genetic epidemiologic studies for the exploration of novel genetic risk variants and genes for cancers. We will focus on numerous genetic epidemiology and large genomics studies using large population-based prospective cohort studies. In order to understand the underlying molecular mechanisms of carcinogenesis, we will apply and develop bioinformatics tools and build statistical models to process large whole genome sequencing and whole exome sequencing, RNA-seq, array-based genotype and epigenetic data to investigate all types of genetic variants, including noncoding and structure variants. The chosen candidate will lead independent research projects in the fields of genetics, epigenetics, functional genomics, and bioinformatics. They should also expect to participate in multiple collaborative projects in cancer-related genetic epidemiology studies.

    The Division of Epidemiology is committed to conducting research to enhance and expand our understanding of the distribution and determinants of disease, to promoting collaboration aimed at the translation of research into cost-effective strategies of disease prevention and health care delivery, and to training independent investigators in epidemiological research and disease prevention. Our group has a broad interest in the research of genetics and genomics for cancer. We concentrate on population-based genetic epidemiologic studies for the exploration of novel genetic risk variants and genes for cancer outcomes. These projects will primarily build from valuable cohort resources based at the Vanderbilt Epidemiology Center, i.e., the Asian Breast Cancer Consortium (ABCC) and the Asian Colorectal Cancer Consortium (ACCC). We are interested in developing and applying computational methods for processing high-throughput genomic sequencing data from the above population-based cohorts to identify various genetic variants, especially structure variants for cancer risk. In particular, we are also highly interested in studying the functional potential of risk coding or noncoding variants by integrating big experimental data from the next-generation sequencing (e.g., ChIP-seq, ATAC-seq, BS-seq and RNA-seq) from public databases (i.e. TCGA and ENCODE). Information about the Division of Epidemiology can be found at https://medicineandpublichealth.vanderbilt.edu/vec/our-team/index.php.

    RESPONSIBILITIES

    Under guidance from Drs. Xingyi Guo and Wei Zheng, the candidate is expected to work on a wide range of bioinformatics projects. He/she should have:
    • A PhD in bioinformatics, computational biology, biostatistics, genomics, molecular biology or related fields. The candidate should have a strong background in processing high-throughput genomic and genetic data with biostatistics knowledge.
    • Strong experience with script languages such as Perl, Python or R. Experience with the Linux/Unix environment is required.
    • Experience in statistical computing (e.g. R/Bioconductor and Biopython).
    • Good interpersonal skills.
    • An excellent grasp of English, both in writing and speech.

    COMPENSATION

    Salary is commensurate with the NIH pay scale. The postdoc positions will be provided with benefits following Vanderbilt University Medical Center standards.

    HOW TO APPLY

    To apply, please send a cover letter, CV, summary of past work, and the names and email addresses of three references to Dr. Xingyi Guo at xingyi.guo[at]vanderbilt.edu. The position is for two years with the possibility of further extension.

    DEADLINE

    The deadline for applications is July 30, 2017. Any applications received after this time will not be considered. Incomplete applications will not be considered.

    POLICY

    Vanderbilt University Medical Center wishes to reflect the diversity of society and welcomes applications from all qualified candidates, regardless of personal background.

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