Required Qualifications:
Ph.D., M.D. or an equivalent terminal or doctoral degree.
EOE Statement:
Washington University is an Equal Opportunity Employer. All qualified applicants will receive consideration for employment without regard to race, color, religion, age, sex, sexual orientation, gender identity or expression, national origin, genetic information, disability, or protected veteran status.
Post Doc Instructions:
Please do not submit an application to this posting.� To apply for this postdoctoral research opportunity, follow the directions below in �Applicant Special Instructions�.
Department Name/Job Location:
This position is in the Department of Neurosurgery.� The position is located at the Medical School Campus.
Essential Functions:
POSITION SUMMARY: 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 -- 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 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. PRIMARY DUTIES & RESPONSIBILITIES: - Implement and develop quantitative methods to analyze, interpret, and visualize single-cell RNA-sequencing data and spatial transcriptomic data.
- Analyze WGS and exome data using pre-existing pipelines on a local linux cluster and in the cloud.
- Integrate genetic and epigenetic information about tumor samples, including mutation, gene expression, and methylation data.
- Develop and perform integrated pathway and gene network analyses to improve interpretability of genomic data.
- Evaluate and design experimental plans for sequencing-based projects studying the genetic basis of cancer.
- Communicate with collaborators, read the literature, learn about new technologies and methodologies, and write scientific publications.
Applicant Special Instructions:
Interested candidates should submit their curriculum vitae, statement of research interests, and contact information for three references via e-mail to Dr. Allegra Petti (allegra.petti@wustl.edu).
Benefits:
This position is eligible for full-time benefits. Please click the following link to view a summary of benefits: https://hr.wustl.edu/benefits/.
Salary Range:
Base pay commensurate with experience.
Internal Applicant Instruction:
Please attach a copy of your most current signed performance evaluation (completed within the last 18 months) to your online account. If you have not received a performance evaluation, you may provide two current signed letters of recommendation (written within the last 18 months), preferably to include one letter from either a current or recent former supervisor. To attach these documents, go to: My Career Tools, Add Attachment, Attachment Type – Performance Reviews or Letters of Recommendation.
Pre-Employment Screening:
All external candidates receiving an offer for employment will be required to submit to pre-employment screening for this position. Current employees applying for a new position within the university may be subject to this requirement. The screenings will include a criminal background check and, as applicable for the position, other background checks, drug screen, employment and education or licensure/certification verification, physical examination, certain vaccinations and/or governmental registry checks. All offers are contingent upon successful completion of required screening.
Preferred Qualifications:
- Doctoral degree in computational biology, bioinformatics, computer science, statistics, biology, or a related field.
- Solid background in both programming and biology, and some background in machine learning and/or statistics.
- 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.
- Previous experience in cancer genomics would be an advantage.
- Motivated, adept at critical thinking, collaborative, and eager to acquire new knowledge and skills on a regular basis.
- Ability to analyze and interpret results, communicate with others, and produce scientific publications.
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