We are seeking highly motivated students and postdocs with interest in applying computational approaches to problems in RNA biology and medicine. We specialize 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. If you are keen on learning, developing, and applying machine learning methods to analyze RNA structure and function and to rationally design new functional RNAs, our group may be a good fit for you. Projects range from highly algorithmic/mathematical method development to hands-on genomic big data analysis, depending on the individual’s interests and background. UC Davis offers an excellent research and training environment and resources to support postdocs and graduate students and is committed to fostering an inclusive, diverse, and safe environment for students and trainees.
We have PhD projects for students with computational background and interests. Students from all UC Davis graduate groups are welcome to inquire with Prof. Aviran (saviran at ucdavis dot edu) about their potential fit to the lab. The Biomedical Engineering, Integrated Genetics & Genomics, Biostatistics, Biological Systems Engineering, Chemical Engineering, Applied Math, and Biophysics graduate groups are particularly relevant.
We are seeking 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. Successful candidates will join a large, diverse, and collaborative Genome Center and a vibrant Biomedical Engineering department at UC Davis.
Qualifications. We are looking for highly motivated and enthusiastic individuals with excellent academic track record, including first-author publications. 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 important problems in RNA biology and RNA medicine. Applicants should also demonstrate excellent writing and communication skills in English.
To apply. Interested candidates should submit a cover letter stating their interests in our research, a CV with list of publications, and contact information for three or more references to Prof. Aviran (saviran at ucdavis dot edu). Informal inquiries are welcome. Applications will be accepted immediately, and review will continue until the positions have been filled by outstanding candidates.
Students with interests and background in math and/or computing are encouraged to contact Prof. Aviran (saviran at ucdavis dot edu). Please state your interest in our research and send a CV, including your GPA, relevant coursework, and previous research/work experience.
About BME, Genome Center, and UC Davis
UC Davis is ranked 5th among US public universities, and the Department of Biomedical Engineering is ranked 14th in the nation in research expenditures by NSF. The department benefits from close collaborations with the School of Medicine, School of Veterinary Medicine (ranked 1st worldwide), Genome Center, Institute for Regenerative Cures, Center for Neuroengineering and Medicine, and the Center for Interventional Biophotonic Technologies.
Genomics and Computational Biology are areas of traditional strength and strategic growth at UC Davis. In particular, it is home to a large and diverse Genome Center, the Center for Population Biology, and the AI Institute for Food Systems.
Biotechnology research at UC Davis is also an area of strength, where graduate students have the opportunity to pursue a doctoral degree with a designated emphasis in Biotechnology, and trainees benefit from the school’s proximity to the San Francisco Bay Area, which is a major biotechnology, data science, and computational biology industry hub. This affords easy access to a vast range of internship and employment opportunities as well as collaborations with industry. UC Davis is characterized by a highly collaborative spirit. Its research community also benefits greatly from the structure of graduate groups, where graduate programs are organized as interdisciplinary units. This gives students and faculty freedom and flexibility to transcend departmental boundaries. You can take a virtual tour of our campus.
Location, location, location
Davis is a small, bike-friendly town in Northern California located within easy reach of San Francisco, Napa Valley, Lake Tahoe, the California coast, and Yosemite. The Davis area offers a variety of cultural and outdoor activities, reasonable cost of living, conformable Mediterranean climate, and an excellent public school system, which is ideal for postdocs with families.