Postdoctoral Research Associate At Princeton University
Position Summary: Princeton University, Terrestrial Hydrology Research GroupThe Department of Civil and Environmental Engineering at Princeton University seeks highly motivated candidates to fill one or more postdoctoral research or more senior research positions. The areas of research include (i) seasonal hydrological forecasting that includes developing hydrological forecasts based on seasonal forecasts from the NCEP Climate Forecast System as well as the North American Multi-model Ensemble NMME) system; (ii) high resolution, process resolving land surface modeling; (iii) quantitative terrestrial remote sensing related to precipitation, soil moisture, evapotranspiration and surface water altimetry; (iv) analysis of climate data related to droughts and the global water cycle.
The position will be in Land Surface Hydrology Research Group (http://hydrology.princeton.edu) under the guidance of Professor Eric Wood and Dr. Justin Sheffield. The position is available immediately and will be an initial 12-month appointment with the possibility of renewal pending satisfactory performance and continued funding. Rank and salary will be commensurate with experience. This position is subject to the University’s background check policy.
Applicants must apply online and should submit a statement of research experience and interest, a current CV with names and contact information (address, email and telephone) of three referees. Please note, responses will only be sent to applicants from whom we seek further information.
Essential Qualifications: The candidate needs to be interested in working collaboratively with other research staff and graduate students within the research group. The successful candidate must have a Ph.D. in a climate-related science or engineering fields with a strong background in hydrologic sciences that includes statistics and probability, demonstrated strong programming skills (such as Python, Fortran, C, Perl, and Shell script) necessary to improve and operate global hydrological models, experience working with large spatial datasets (preferably using GrADS) on multiple computer platforms (Unix/Linux, Windows), and have advanced proficiency in communicating scientific findings in peer-reviewed journals and at professional meetings.
Education Required: Doctorate Degree
For more information and to apply for this job, see the official posting.
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