Job: Postdoc position in Quantitative Evolutionary Genetics and Ecoinformatics

Department: DPB – Plant Biology

Salary: TBD

Location: Stanford, CA

We aim to recruit a highly motivated and creative person with strong training in quantitative or population genetics / evolutionary biology / bioinformatics / computer science.

We seek to understand the impacts of climate change on the genetic diversity and evolutionary potential of plant species. Specifically, we strive to experimentally understand the mode and tempo of genetic adaptation to climate, find genetic loci involved in past adaptations and model evolving populations using population genetic theory and computational approaches. Possible projects include the analysis of next generation sequencing data to track evolution of experimental populations subject to different climates (GrENE-net.org), the development of new predictive evolutionary rescue models in population genetics, or modeling satellite imagery and public biodiversity databases using deep neural networks (see www.moisesexpositoalonso.org/research). This position involves conducting research independently, working with large genomic and biodiversity datasets, being involved in collaborative projects, preparing publications, and presenting research in scientific meetings. We prefer candidates interested in strengthening connections between molecular ecological genetics and computational biology, who will be active members of the research community at the Carnegie Plant Biology and Global Ecology departments, and the Stanford Biology, Genetics and Earth Systems departments.

This is a full-time position with competitive salary and benefits. The lab is located at the Carnegie Institution on Stanford campus. Carnegie Postdocs have access to Stanford facilities. Stanford campus is a vibrant community embedded in the San Francisco Bay area, with opportunities for extensive social and scientific interactions. The initial position will be for one year with potential renewal of up to three years depending on performance.

Required qualifications for this position are a doctoral degree in population genetics, evolutionary biology, ecology, bioinformatics, computer sciences, or statistics, fluency in a major programming language, a track record of research productivity and independence, and willingness to work closely with collaborators and lab members.

Informal inquiries about this position can be made by emailing Moises (Moi) Exposito-Alonso at moisesexpositoalonso@gmail.com. To be formally considered, please include a cover letter and CV, and indicate 3 referees that I can ask for letters of recommendation.

Additional information:

The Department of Plant Biology of the Carnegie Institution is located on the campus of Stanford University. Formerly known as the Carnegie Institution of Washington, the Carnegie Institution for Science is a U.S.-based non-profit, private endowment. Andrew Carnegie founded the Carnegie Institution of Washington in 1902 as an organization for scientific discovery to serve as a home to exceptional individuals – men and women – with imagination and extraordinary dedication capable of working at the cutting edge of their fields. Today, Carnegie scientists work in six scientific departments on the west and east Coasts and at the Las Camapanas Observatory in Chile. Carnegie investigators are leaders in the fields of plant biology, developmental biology, Earth and planetary sciences, astronomy, and global ecology. The Department of Plant Biology and Department of Global Ecology have state-of-the-art facilities for molecular genetic studies of plants and computer resources. To learn more about the Department of Plant Biology and Global Ecology, visit https://dpb.carnegiescience.edu and https://dge.carnegiescience.edu.

Carnegie is an equal opportunity employer. All qualified applicants will receive consideration for employment without regard to race, religion, color, national origin, sex, sexual orientation, gender identity, age, veteran status, disability or any other protected status in accordance with applicable laws.