Two postdoctoral fellowships in computational biology are available in Dr. Sylvia Plevritis' Lab located in the James H. Clark Center at Stanford University. The postdoctoral fellowships will involve the development and application of novel computational algorithms that integrate diverse genomic and proteomic cancer datasets, including RNAseq, methylation, and single cell proteomics. One fellow will aim to microenvironment factors that impact cancer progression and therapeutic resistance; the other fellow will work to integrate genomic and imaging data for developing predictive and prognostic signatures of patient outcomes. Both research projects involve reconstructing transcriptional and signaling networks of cancer using high throughput data derived from cellular subpopulations of tumors. Each postdoctoral fellow will work closely with experimental molecular biologists to translate computationally-derived results into experimentally testable hypotheses and analyze the resulting data from the experiments. Candidates must have a strong quantitative background, with a PhD in computational biology, bioinformatics or related field including engineering, computer science, statistics, or mathematics. Strong knowledge in machine learning and programming (C/C++. MATLAB, or R) are required. Knowledge in one or more of the following areas is desirable: gene network reconstruction, Bayesian analysis, sparse regression and survival analysis. Excellent verbal and written communication skills are essential.
Applicants should e-mail a cover letter describing research experience, accomplishments and research interests, CV and 3 references to Ramzi Totah (rtotah@stanford.edu), under the following subject line: "Postdoctoral Fellowship in Computational Biology."
Stanford University is an equal opportunity employer.
