The Yu Lab in the Department of Computational Biology is looking for a highly motivated bioinformatics research scientist to develop and apply computational & systems biology approaches to dissect the molecular circuits that drive tumorigenesis, tumor immune-escape and drug resistance, and identify biomarkers and combination therapies (particularly with immunotherapy) for the treatment of pediatric cancer patients. This scientist will analyze and integrate high-throughput omics data including transcriptomic, genomic, epigenomic, functional genomic, chemical genomic and proteomic data to model context-specific cellular/molecular networks and to identify actionable targets, biomarkers or compounds that could be translated into clinic for the development of precision medicine in pediatric cancer. The scientist will work closely with our pipeline and visualization teams to explore novel analysis approaches for single-cell RNA-Seq, NGS-based RNAi/CRISPR screening, immune-profiling and proteomics data for molecular network inference and target identification. Candidates with a strong interest in cancer precision medicine, and expertise in big data analysis are encouraged to apply. The successful candidate will also have an opportunity to participate in research projects involved in the analysis of the cancer genome, epigenome, transcriptome or proteome. Recognized as a world leader in mapping the genetic landscape of pediatric cancer, the Department of Computational Biology has developed state-of-art computational infrastructure, well-established analytical pipelines, and deep genomic analysis expertise with a track record of high-impact publications in top-tier biomedical journals such as Nature, NEJM, JAMA, Nature Genetics and Nature Methods.
Ph.D. in computational biology, systems biology, bioinformatics, biomedical informatics, computer science, statistics/biostatistics, mathematics, molecular biology, immunology, pathology, biochemistry, or any related field required.
Ph.D which must include research related to bioinformatics (such as analysis of sequence data, microarrays, SNPs, image data, proteomics data, or biological pathways; development of algorithms, statistical methods, or scientific software); OR If Ph.D with no bioinformatics research, then two (2) years of pre-or postdoctoral experience in computational biology or bioinformatics research is required
Experience with programming languages such as Perl, C, or Java required
Experience with omics data analysis using R or Python and familiarity with linux/unix is required. Expertise in parallel computing (spark, hadoop), web development, visualization (R-Shiny, d3) and databases (MySQL, PostrgeSQL) is also highly desirable.
St. Jude is an Equal Opportunity Employer