We are seeking a postdoctoral associate to conduct computational science research in the field of plant biology. Candidates with a strong background in network analysis and scientific computing skills are preferred. Ideal candidates will be able to work well in a team environment, be highly motivated to publish and to acquire new skills.
The DOE project will bridge plant bioinformatics and computational science. On the bioinformatics side it will involve phylogenomics, protein structure, and biochemistry; on the computational side it will involve linear programming, flux balance analysis, and machine learning. The position will involve the development and analysis of a machine learning approach that will allow researchers to identify key enzymes within any plant’s genome-wide metabolic network that will increase the production and yield of important metabolites.
We apply various approaches including gene regulatory network modeling, transcriptomics, genome editing, single-cell biology, whole plant physiology and metabolomics. We have funded positions available for work on single-cell regulation of the circadian clock and the use of computational tools to study temporal regulation of specialized plant metabolites, though students with a broad range of interests are encouraged to contact us to discuss possible projects.
If you are interested in applying, please email Dr. Greenham (greenham [@] umn.edu) your CV and a short (1-2 paragraph) email explaining your research interests and career goals.
Undergraduates Undergraduates interested in whole plant biology, acclimation and to climatic stress, genetics, molecular cloning and bioinformatic techniques and data processing are all encouraged to come work with us! If interested, send Dr. Greenham an email outlining your interests and goals. Undergraduates at the lab have had majors ranging from Plant Biology, Computer Science, Public Health and more.
While we love working with undergraduates, we do encourage students to write to us the semester before they would like to begin as the lab is sometimes full.