Computational biology postdoc position to study transcriptional regulation of metabolism in plants

Carnegie Institution for Science
Plant Biology
United States CA Stanford


A postdoctoral researcher position is available immediately in laboratory of Dr. Sue Rhee at Carnegie Institution for Science, Department of Plant Biology. The project aims to systematically examine the transcriptional regulation of plant metabolism using multiomics approaches. The successful candidate will lead the collaborative project and develop novel computational methods and algorithms for multi-omics datasets integration (e.g. RNA-seq, ChIP-seq, HiC, and ATAC-seq).

The Carnegie Institution, a private, nonprofit organization engaged in basic research and advanced education in biology, astronomy, and the earth sciences, was founded and endowed by Andrew Carnegie in 1902 and incorporated by an act of Congress in 1904. Andrew Carnegie conceived the Institution’s purpose “to encourage, in the broadest and most liberal manner, investigation, research, and discovery, and the application of knowledge to the improvement of mankind.” The Department of Plant Biology engages in basic research on the mechanisms involved in the growth and development of plants and algae. The Department of Plant Biology is co-located with the Carnegie Department of Global Ecology on a seven-acre site on the campus of Stanford University.


Qualified candidates must have a Ph.D. or equivalent in Bioinformatics, Computational Biology, Computer Science, Plant Biology, or a related field, and a strong background in programming, statistics as well as a strong interest in development of new computational algorithms to address interesting biological problems. Candidates with experience in machine learning are especially encouraged to apply. The successful candidates should also have demonstrated ability for independent and critical thinking, excellent communication and teamwork skills, and enthusiasm for learning new knowledge.

Start date

As soon as possible

How to Apply

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