NEW OPPORTUNITY (Fall 2023)

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Multiple Ph.D. and Postdoctoral Positions in Snowfall Remote Sensing

University of Minnesota Twin Cities

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Work Environment: The Hydrologic Sciences and Remote Sensing (HydSens) group, led by  Ardeshir Ebtehaj, is part of the Civil, Environmental, and Geo-Engineering Department and the Saint Anthony Falls Laboratory at the University of Minnesota Twin-Cities. The team works on several research areas including passive microwave remote sensing of global precipitation and soil-snow-vegetation continuum as well as novel methodologies and mathematical frameworks for improved short and long-term weather and hydrologic forecasts through data assimilation and deep learning. For more information, please visit our website at https://www.hydsens.com/. 

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Project and Position: Dr. Ebtehaj has been selected to serve as the Principal Investigator on a NASA-funded project titled “A Multi-Decadal Satellite Snowfall data RecOrd (MAESTRO)”. The project is collaborative between the University of Minnesota, Goddard Space Flight Center, and the Jet Propulsion Laboratory. The project also has collaborators in the National Oceanic and Atmospheric Administration, the Institute of Atmospheric Sciences and Climate (CNR-ISAC) in Italy, and the Tokyo Institute of Technology. The project scope includes funding for multiple Ph.D. and Postdoctoral positions that will perform work closely with Dr. Ebtehaj, and other collaborators of the projects. This project aims to use a constellation of NASA and NOAA satellites to provide the longest data record of global snowfall to better understand how the precipitation phase has changed in the past four decades in response to global warming. The position will consist of yearly contracts, renewable for up to five years depending on funding availability, adequate research performance, and positive contributions to the project.

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Required skills and prerequisites: Background in Civil and Environmental Engineering, Hydrology, Earth/Atmospheric Science, Computer Science, Physics, and Applied Mathematics. Strong writing and communication skills are also required, as is the ability to work independently and collaboratively. Experience in programming and analyzing data in MATLAB or Python or a similar technical programming language is required. Past experiences in precipitation processes, microwave and infrared remote sensing, satellite data analysis, radiative transfer modeling, Bayesian and frequentist statistics, linear and non-linear optimization, machine learning, and neural networks are advantageous.   

Applicants should send the following materials to Ardeshir Ebtehaj at ebtehaj@umn.edu: CV, contact information of at least two references. The result of the TOEFL test is needed for most international Ph.D. applicants. Applicants are highly encouraged to send the results of any available standardized test that measures the general mental ability of an individual such as the GRE test – especially the quantitative part.  The start date is immediate (Fall 2023) but can be flexible.

 

Note: Unfortunately, I will not be able to reply to all received applications. I will reach out only to those applicants that fit the required qualifications.