Situated in a highly dynamic research environment at Stanford University in the Departments of Medicine (Oncology) and Genetics, The Curtis laboratory (http://med.stanford.edu/curtislab.html) is seeking a highly motivated computational scientist to join the Cancer Systems Biology group. Our research couples state-of-the-art computational and experimental techniques to characterize the evolutionary dynamics of tumor progression, to delineate the cancer genotype:phenotype map and to define novel therapeutic targets and biomarkers.
The successful candidate will be part of an interdisciplinary research team developing novel technological and methodological approaches to improve the diagnosis, treatment and earlier detection of cancer. He/she will develop and apply computational and statistical methods to interpret high-throughput ‘omic’ data, including whole genome, methylome, RNA-seq, ATAC-seq, and single cell data, as well as other emergent technologies. A unifying theme of our research is to exploit ‘omic’ data derived from clinically annotated samples in robust computational frameworks coupled with iterative experimental validation in order to advance our understanding of cancer systems biology. Our research has a strong translational focus and the successful candidate will interact closely with clinicians and experimental biologists to test, validate, and refine hypotheses both within Stanford and beyond. This is a fantastic opportunity for a motivated computational scientist to join a dynamic team with significant opportunities for scholarship and leadership.
Description of responsibilities: • Develop, deploy, and maintain computational pipelines for high-throughput omic analyses • Evaluate the performance of novel technology platforms and assays • Manage and archive large genomic data sets • Interact with experimental scientists to develop and test hypotheses and design experiments • Present results and progress updates, contribute to manuscript preparation • Attend seminars and review current literature to remain up to date on advances in cancer genomics
Requirements: PhD degree in computational biology, bioinformatics, statistics, or computer science or a MS degree (or equivalent) with at least 3 years of experience in bioinformatics/software development. Strong analytic and communication skills, as well as broad experience with multiple programming languages, bioinformatics software and databases are essential. A relevant publication record is expected. Salaries are competitive and commensurate with experience and qualifications. Interested and qualified applicants should send a Cover Letter, Curriculum Vitae and three Letters of Reference to Prof. Christina Curtis (email@example.com).