I am recruiting 1 graduate student to join my lab beginning January 2022. This student will be supported in part by an NSF grant and will engage in a project to explore how warming influence plant-fungi interactions and negative density dependence at one of the first tropical warming experiment in the world: TRACE (https://www.forestwarming.org). Competitive applicants should have a strong interest in community ecology as well as a commitment to contributing to a collaborative, inclusive and fun learning environment. A master’s degree, some experience with shade house experiments, as well as comfort with statistical modeling using R are preferred.
If your passions involve plant, insects, and fungi, the Bachelot Lab is for you! Research in the lab is focused on plant demography, species interactions, coexistence, and global change biology, with emphasis on plants, insects, and fungi. Current projects are examining:
- effects of enemies (herbivores, pathogens, etc.) and mutualists on plant communities
- effects of altered climate on species interactions and coexistence
- roles played by enemies and mutualists along succession
- coexistence theory
For more information about research in the lab and recent publications, see http://bachelotlab.com/. A major theme of the lab is combining field observations, theoretical methods, and genomic approaches to tackle ecological questions. Prospective students with strong quantitative skills and experience or interest in theoretical ecology and theory/data interface are especially encouraged to apply.
The Department of Plant Biology, Ecology and Evolution at Oklahoma State University is home to a collegial and vibrant community of scholars. We have an unusually strong concentration of faculty and students studying the plant biology from the molecular to the ecosystem scales (https://plantbio.okstate.edu/). We are located in Stillwater, OK, a diverse, affordable, and friendly city.
A master’s degree, some experience with shade house experiments, as well as comfort with statistical modeling using R are preferred.