A postdoctoral researcher position is available immediately in the laboratory of Dr. Sue Rhee at the Carnegie Institution for Science, Department of Plant Biology, to create and analyze metabolic models with a focus on plants covered at Plant Metabolic Network (PMN, www.plantcyc.org). Plants are the foundation of many industrial sectors and a better understanding of their metabolism by simulation will impact our way on how we use plants for our benefit. The successful candidates will lead the development of computational tools and methods for converting the present tools and databases at Plant Metabolic Network (PMN, www.plantcyc.org) for metabolic modeling with subsequent large-scale analysis of the created networks and models testing hypotheses regarding the evolution of plants and their metabolic pathways.
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, Biology, Plant biology, Microbiology, Systems Biology, Biochemistry or a related field, and a strong background in reconstructing constraint based metabolic models, statistics and programming, as well as a strong interest in plant metabolism and its biochemistry and in development of new computational approaches to address interesting biological problems. Candidates with experience in programming in MATLAB and/or the use of the COBRA toolbox are especially encouraged to apply. Working experience (either wet lab or dry lab) with plants, phylogenomics, use of high performance computers (clusters), and proficiency in programming languages of Python and/or Perl are pluses. The successful candidates should also have demonstrated ability for independent and critical thinking, excellent communication and teamwork skills, and enthusiasm for learning new things.