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.
Department Name/Job Location:
This position is in the Department of Radiation Oncology. This position is for the Medical School Campus.
Essential Functions:
POSITION SUMMARY: The Washington University School of Medicine, Department of Radiation Oncology, invites talented post-doctoral candidates with a background in genomic data analysis, algorithm design, and/or machine learning to apply for a position in Dr. Jin Zhang’s translational genomics lab (https://sites.wustl.edu/jinzhang). The candidate will play a critical role in finding new discoveries and developing advanced genomic and data science approaches in cancer biology as applied in personalized radiation therapy (RT). The position offers an excellent opportunity to conduct research in a supportive and stimulating environment, closely collaborating with computer scientists, biologists, and clinicians within Department of Radiation Oncology and other institutes across the campus, including the McDonnell Genome Institute, Institute for Informatics, and Siteman Cancer Center. PRIMARY DUTIES AND RESPONSIBILITIES: - Develop hypotheses and design novel genomics and data science approaches in translational cancer genomics.
- Establish and execute pipelines through developing novel algorithms and integrating existing bioinformatics tools using next-generation sequencing and other omics data.
- Prepare and present results of research in internal seminars and external conferences and journals.
- Assist with grant preparation and reporting.
- Train research assistants in the lab and work with other researchers in applying the informatics tools we develop.
Required Qualifications:
Ph.D. (or equivalent degree) in bioinformatics, genomics, computational biology, computer science, machine learning, or related field to be considered.
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�.
Salary Range:
Base pay commensurate with experience.
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.
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/.
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.
Applicant Special Instructions:
Interested candidates should send a cover letter (brief) and curriculum vitae to Dr. Jin Zhang at jin.zhang@wustl.edu.
Preferred Qualifications:
- Experience with bioinformatic algorithm development and/or bioinformatic data analysis.
- Proficiency in a programming language, such as Python, C++, and/or Perl.
- Proficiency in a statistical programming language, such as R and SAS.
- Experience with scientific computing and data visualization tools.
- Highly motivated with excellent oral and written communication skills.
- Understanding of current next-generation sequencing technologies.
- Understanding of statistical techniques for differential expression, gene set enrichment analysis, clustering, outcome analysis, and multivariant analysis.
- Experience with Git, Docker, and Cloud computing.
- And/or understanding concepts and techniques in machine learning with Scikit-Learn, Keras, and/or TensorFlow.
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