A postdoctoral scholar position in Single-Cell Cancer Genomics is available in the laboratory of Dr. Allegra Petti at Washington University School of Medicine. We use computational approaches to analyze, integrate, and interpret large-scale genomic data -- with an emphasis on single-cell RNA-sequencing data -- to better understand heterogeneity and gene regulatory networks in human cancer. We participate in long-term, data-rich collaborations with established labs at Wash. U., in which quantitative analysis is closely integrated with clinical studies and molecular biology. The postdoctoral scholar will be involved in projects that address topics such as intratumoral expression heterogeneity and tumor evolution in acute myeloid leukemia, and the interplay of genetic, epigenetic, and immunological heterogeneity in solid tumors such as glioblastoma. Opportunities to initiate and lead projects, publish, participate in ongoing group projects, and be co-mentored by faculty collaborators are plentiful.
PRINCIPAL DUTIES & RESPONSIBILITIES:
1. Implement and develop quantitative methods to analyze, interpret, and visualize single-cell RNA-sequencing data.
2. Analyze WGS and exome data using pre-existing pipelines.
3. Integrate genetic and epigenetic information about tumor samples, including mutation, gene expression, and methylation data.
4. Develop and perform integrated pathway and gene network analyses to improve interpretability of genomic data.
5. Evaluate and design experimental plans for sequencing-based projects studying the genetic basis of cancer.
6. Communicate with collaborators, read the literature, and produce scientific publications.
Applicants must have a doctoral degree in computational biology, computer science, statistics, physics, applied math, bioinformatics, or a related field, with a solid background in programming, and some background in machine learning and/or statistics. Candidates must be comfortable working on a UNIX/Linux operating system, program in Perl and/or Python, and have experience with statistical analysis packages (R, Bioconductor) and bioinformatics tools. A working knowledge of genetics and molecular biology is required. Previous experience in cancer genomics would be an advantage, but is not essential. The successful candidate will be self-motivated, adept at critical thinking, collaborative, and eager to acquire new knowledge and skills on a regular basis. The ability to analyze and interpret results, communicate with others, and produce scientific publications is essential.
Interested candidates should submit their curriculum vitae, statement of research interests, and contact information for three references via e-mail to Dr. Allegra Petti (email@example.com).