We are looking for a highly motivated quantitative scientist interested in directing their career toward interdisciplinary biomedical research. This is a great time to veer your career into this rapidly growing area since we are facing a shortage of scientists with the analytical and computational background to take advantage of the enormous amount of genomic and health data generated. Two large initiatives Big Data to Knowledge and Precision Medicine by the NIH show the commitment of the US government in investing in these areas.
The candidate would receive training in biomedical research and work on developing statistical and computational methods to sift through the enormous amounts of genomic data. The short-term goal is to develop prediction models for disease risk and drug response and to discover the biology underlying these traits. The ultimate goal is to translate these models and discoveries to improve treatment of patients and inform disease preventive interventions.
- A PhD degree in computer science, bioinformatics, physics, engineering, statistics, or other quantitative disciplines with interest in applying skills to biomedical research. Or working toward such degree.
- Strong analytical, statistical, quantitative, and computational/programming skills. Should be comfortable with large data sets, distributed computing, and databases.
- Skills in scripting languages (Python, Perl), database management (MySQL), statistical software (R), Angular.js, Meteor.js.
- Candidates with a multidisciplinary background, spanning both life sciences and quantitative sciences are especially encouraged to apply.
To formally apply, please send CV in PDF format to Hae Kyung Im (haky at uchicago.edu).