Postdoctoral Fellow Position in Computational and Statistical Genomics
University of California Riverside
USA-CA
The postdoctoral fellow will focus on developing computational and statistical methods for big data problems motivated from genomics and epigenomics. Possible research projects include modeling the 3D chromatin architecture using Hi-C data, integrating chromatin structure with ChIP-seq, RNA-seq and other functional genomics assays, and investigating the interplay between genome architecture and gene regulation. The postdoctoral fellow will have the opportunity to collaborate with a variety of research groups at the UC Riverside and elsewhere.
The position includes a generous benefits package. Starting date is flexible. Visa sponsorship is available for non-US candidates.
Qualifications
An ideal candidate would have:
• a recently completed PhD degree in closely related area (computer science, statistics, biostatistics, applied mathematics, computational biology, or bioinformatics)
• strong training in quantitative modeling (machine learning, Bayesian inference, etc.) or computational genomics experiences (high-throughput sequencing data analysis, algorithm development, etc.)
• proficiency in at least one programming language (Python, C/C++, Java, Matlab, or R)
• a track record of publication in peer-reviewed journals
• good spoken and written communication skills
Job Information
Start Date: September 01, 2020
Duration: Full Time
Status: Open
Contact Information
University of California Riverside
Department of Statistics
wenxiu.ma@ucr.eduhttp://faculty.ucr.edu/~wenxiu/openings.html How To Apply:
Interested applicants should submit a CV, a brief research statement, and contact information of three references to Dr. Wenxiu Ma at wenxiu.ma@ucr.edu. In your cover letter, please discuss why you are interested in this position.