Our group is looking for a postdoc! One of the main research threads in our group (see the research tab) concerns the development and use of microwave remote sensing-based proxies of vegetation water content, which is expected to depend on leaf water potential. The vegetation water content proxies have been used for a range of applications related to vegetation water stress response.
The postdoc would work in one of three areas: a) building new retrieval algorithms to determine vegetation water content or leaf water potential from passive and active microwave remote sensing, using physically based and/or machine learning approaches, b) data assimilation of microwave observations into a plant hydraulics-enabled model or c) use of microwave remote sensing to gain process insight into plant-water coupling. Work in this last area is subject to the right fit between questions of interest to the candidate and the group's funding.
If you have strong computational and communication skills and experience working with microwave remote sensing, retrieval of geophysical variables, data assimilation, plant hydraulics, and/or plant responses to water stress, you may be a great fit for this postdoc. To apply, please send a cover letter and CV to Alex Konings at firstname.lastname@example.org. In your cover letter, please explain what aspects of the position you would be most excited to work on and why. The pay is commensurate with experience, and is adjusted for the high cost of living in the Palo Alto, CA area where Stanford is located. An in-person appointment would be strongly preferred, although a partially remote position (if the candidate is based in the US) could be discussed. Applications will be reviewed as they are received. Please apply by January 10th, 2023 to receive full consideration.
Stanford University as a whole, and the Remote Sensing Ecohydrology Group in particular, is an equal opportunity employer and is committed to increasing the diversity of its staff. Our research group welcomes applicants from all backgrounds, and we are particularly interested in candidates from groups that are historically underrepresented in science.