Postdoctoral Research Associate (Genomics and Data Science)

Washington University School of Medicine
Radiation Oncology
United States MO 63110
wustl.edu/

Description

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 (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.


Qualifications

* Ph.D. (or equivalent degree) in bioinformatics, genomics, computational biology, computer science, machine learning, or related field to be considered.
* 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.


Start date

To be determined

How to Apply

Interested candidates should send a cover letter (brief) and curriculum vitae to Dr. Jin Zhang at jin.zhang@wustl.edu.


Contact

Jin Zhang
jin.zhang@wustl.edu

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