We are seeking a bioinformatics programmer with a computer science background. The successful candidate will demonstrate strong programming skills (experience in Java required, functional programming a plus) and an interest in deep learning. Neither prior experience in bioinformatics or background in biology is required for this position. When you join the laboratory, you will join a small team including a senior software engineer and another programmer to help develop new data analysis methods using deep learning approaches. Software developed in the laboratory helps a diverse range of scientists perform data analysis. You will have the opportunity to work on projects from inception and design to the maintenance phases. Mentoring for aspects of biology and bioinformatics relevant to the project will be provided. This position is a good opportunity to engage in research in bioinformatics and prepare a strong application to graduate school.
The Campagne laboratory is located at the Weill Cornell Medicine, in the space of the Institute for Computational Biomedicine (http://campagnelab.org, 1305 York Ave, NY, NY 10065). Our laboratory is actively developing scalable computational approaches that facilitate the analysis of high-throughput sequencing data. Please address your resume and cover letter to Fabien Campagne (see contact information on this web site).
Start date: Sept-October 2016
Students enrolled in one of following Weill Cornell graduate programs can contact the PI to apply for rotations in the lab:
- The Tri-I Training Program in Computational Biology and Medicine
- The Tri-Institutional MD-PhD Program
- The Physiology, Biophysics and Systems Biology PhD Program
Other students interested in joining the laboratory are encouraged to apply to these programs and mention the laboratory in their application package.
We have a number of ongoing projects to which rotation students can contribute. Example of current projects include:
- Development of efficient, fully parallel methods to reliably identify sequence variants that differ across groups of samples in NGS data.
- Development of a pipeline to analyze RRBS data (NGS protocol to measure DNA methylation at the base level) in single samples and differences between groups of samples
- Analyze NGS small RNA and messenger RNA data from kidney transplant biopsies to help design a non-invasive diagnostic.
- Study relevant animal models of Late Onset Alzheimer’s disease with NGS methods to elucidate mechanisms of neurodegeneration.
We are working on many projects concurrently, so there is always an interesting rotation project available if you are interested in working in the lab. We are more likely to accept rotation students when we have funding for one student to continue working on the project for his/her thesis, as is currently the case.