Aviran Lab, Genome Center and Department of Biomedical Engineering
Postdoc
Description
Postdoctoral Positions in Computational RNA Biology and Medicine at UC Davis
Two postdoctoral positions are available in Dr. Sharon Aviran’s research group at UC Davis, starting early 2023. The Aviran group specializes in the development of statistical models and machine learning algorithms to infer predictive models of RNA folding and RNA function based on high-throughput biological data and in application of these methods in large-scale genomic data analyses. We are seeking highly qualified computational scientists to work on two collaborative NIH-supported projects involving modeling of folding thermodynamics for mRNAs with modified nucleotides (in the context of mRNA therapies) and transcriptome-wide mechanistic studies of RNA helicase binding (RNA-protein interactions). The research on RNA folding will be carried out in collaboration with Prof. David Mathews at the University of Rochester. The research on RNA-protein interactions will continue to be carried out in collaboration with Prof. Elizabeth Tran at Purdue University.
To Apply: Interested candidates should submit a cover letter stating their interests in our research, a CV with a list of publications, and contact information for three or more references to Prof. Aviran (saviran at ucdavis dot edu). Successful candidates will join a large, diverse, and collaborative Genome Center and a vibrant Biomedical Engineering department at UC Davis. For more information, please visit https://aviranlab.bme.ucdavis.edu/open-positions-2023/.
Required / Preferred Qualifications
We are looking for highly motivated and enthusiastic individuals with excellent academic track record. Candidates should have, or be in the process of completing, a PhD in computational biology, statistics/biostatistics, genomics, computer science, biophysics, bioengineering, electrical engineering, applied math, or related fields. Strong analytical and programming skills are required. Preference will be given to candidates with experience in machine learning, statistical analysis, and/or genomic data analysis. Ideal applicants should be creative, independent, enthusiastic about research, able to work as part of a multidisciplinary team, and excited by the development and application of computational methods to address important problems in RNA biology and medicine. Applicants should also demonstrate excellent writing and communication skills in English.
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