A Computational Programmer / Analyst is sought by a world-recognized leader in nutrigenomics at Tufts University in Boston, MA, to contribute to a funded project seeking to identify where and how genetic variation, diet and exercise influence risk of heart disease and type 2 diabetes.
Synopsis of the project:
The influence of genetic variation on human disease risk is incompletely defined and lifestyle choices such as diet and exercise are important modulators of that risk. We use nutrigenomics and genome-wide applications to define those genetic factors pertinent to risk of cardiovascular disease, type 2 diabetes and obesity that are sensitive to diet, exercise and other lifestyle choices. An expansion of our work, newly funded, brings in the application of systems biology approaches and statistical genetics methodology to predict the impact of dietary components and physical activity in modifying the disease risk of common genetic variants in a genome-wide manner. Gene networks, built from specific gene-environment interactions, will be analyzed for pathway enrichment and pertinent gene co-expression in order to predict new sites of gene-environment interactions. A long-term goal of this research effort is to redraw gene networks and pathway diagrams to include genetic variants, environmental factors and allele-specific connections between the linked entities so that pathway fluxes and disease status can be better depicted.
Successful identification of gene-diet interactions will result in a more complete understanding of how the human genome senses the environment and how disease risk conferred by genetic variation is modulated.
Who we are:
- A highly successful laboratory conducting research at the intersection of human nutrition and genomics
- Research focus on cardiovascular disease, type 2 diabetes and their risk factors, especially as influenced by genetic variation and the modulating response of diet and physical activity
- An innovative, collegial and highly collaborative group
- Excellent track record of publishing and obtaining external funding
What you bring to the group:
- A PhD in Computational Biology, Molecular Biology, Genetics, Biostatistics or related field with a minimum of three years' post-graduate experience
- Success working cooperatively and effectively with other scientists
- Knowledge of statistics and genetics
- Demonstrated skills in bioinformatics programming in Perl, C++, Python or Java Experience in a Linux, Unix or Ubuntu environment
- Working knowledge in R is desirable
- Expertise with large, genome-wide datasets, and their manipulation and analysis
- Record of peer-reviewed publications
- Excellent verbal and written communication skills
What we offer:
- An NIH-funded position to develop applications for the genome-wide prediction of gene-environment interactions with respect to diseases of a metabolic nature.
- Competitive salary with a wide range of benefits.
- Congenial, academic setting.
- An environment where your creativity becomes a valuable and sought after part of ongoing projects and partnerships.
Tufts University is an EEO.
Interested candidates should submit a cover letter and CV to Dr. Larry Parnell at larry.parnell@tufts.edu. Please refer to job code: TH0701.
Support for visa applications for persons not currently residents of the USA will not be considered.
