Post-Doctoral position in modelling of snow-land-climate interactions and their response to climate change
The climate modelling and analysis group based in the department of Geography and Environmental Management at the University of Waterloo, Canada invites applications for a full-time (1.0 FTE), 12-month, fixed-term Post-Doctoral Fellow (PDF) research position in modelling of snow-land-climate interactions and their response to climate change. For more details about our research group see <https://uwaterloo.ca/scholar/c5fletch/>. The PDF will be engaged in two projects. The first involves the implementation and analysis of a suite of global land surface model simulations using the Community Land Model (CLM) to assess the impact of snow process parameterizations on climate. The second project involves the analysis of the CMIPx suite of model output to characterize projected land surface hydrological responses to climate change and their impact on the frequency and intensity of future drought in Canada. The position is partially supported by CanSISE (<http://www.cansise.ca>), a Canada-wide network of researchers from academia and government, engaged in climate modelling efforts related to quantifying sea ice and snow evolution. The position will involve collaboration internally within the research group at Waterloo, and externally with colleagues in CanSISE, at Environment and Climate Change Canada (<https://www.ec.gc.ca>), and at Agriculture and Agri-Food Canada (<http://www.agr.gc.ca/>).Essential requirements: the PDF must have (or be about to obtain) a Ph.D. in atmospheric science, physics, chemistry, applied mathematics, or a related field. Experience analysing and visualising large climate/geophysical datasets, preferably in netCDF format, using a scientific programming language such as Python, IDL, Matlab, or NCL in a Linux computing environment. The PDF will be a highly effective oral and written communicator, and be able to work as part of a research team. Desirable requirements: Experience running simulations with global or regional models of the atmosphere and/or land surface would be a distinct advantage, particularly with any of the NCAR Community Earth System Model (CESM) suite. Knowledge of advanced multivariate statistical methods, and/or statistical learning techniques such as support vector regression would also be an asset.The position has an anticipated start date of September 5, 2017, or as soon as possible after that date. The initial appointment will be for one year, with the possibility of renewal based on performance. A review of applications will begin immediately and will continue until the position is filled. To apply, please send a single document in PDF format containing a cover letter summarizing your research interests and career goals, current CV, and contact information for three references to Prof Chris Fletcher (<firstname.lastname@example.org>). We regret that only applicants being called for interview will be contacted.