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We are seeking highly motivated students 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. Graduate StudentsWe 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, Applied Math, Biostatistics, Integrated Genetics & Genomics, Biophysics, Biological Systems Engineering, and Chemical Engineering graduate groups are particularly relevant. Undergraduate StudentsStudents 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 DavisUC 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, locationDavis 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. |