A postdoctoral scholar position in Computational 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 genomic data -- with an emphasis on single-cell RNA-sequencing data and spatial transcriptomic data -- to better understand intratumoral heterogeneity, the immune microenvironment, 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 use cutting-edge techniques to address topics such as the interplay of genetic, transcriptional, spatial, and immunological heterogeneity in brain tumors (e.g. glioblastoma). Opportunities to initiate and lead projects, develop new analytic methods, publish, participate in ongoing group projects, and be co-mentored by faculty collaborators are plentiful.
Principal Duties and Responsibilities:
1. Implement and develop quantitative methods to analyze, interpret, and visualize single-cell RNA-sequencing data and spatial transcriptomic data.
2. Analyze WGS and exome data using pre-existing pipelines on a local linux cluster and in the cloud.
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, learn about new technologies and methodologies, and write scientific publications.
Environment: The postdoc will work in a highly collaborative environment, involving extensive interaction with computational biologists, programmers, molecular biologists, clinicians, and other faculty at Washington University in St. Louis.
Salary range: The hiring range for this position is commensurate with experience.
Benefits: This position is eligible for full-time benefits. Please visit the Human Resources postdoctoral benefits page for more information.
EOE statement: Washington University in St. Louis is an equal opportunity, affirmative action employer and encourages applications from women, ethnic minorities, veterans and individuals with disabilities.
Required qualifications: A doctoral degree in computational biology, bioinformatics, computer science, statistics, applied math, biology, or a related field, with a solid background in programming and some background in machine learning/statistics, is required. Working knowledge of molecular biology and cell biology is required. 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.
Preferred qualifications: 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. Previous experience and a track record in cancer genomics strongly preferred.
Interested candidates should submit their curriculum vitae, statement of research interests, and contact information for three references via e-mail to Dr. Allegra Petti (firstname.lastname@example.org).