University of Maryland is seeking a postdoctoral associate to support the dynamic crop growth
modeling for a project funded by the United States Department of Agriculture (USDA)/National
Institute of Food and Agriculture (NIFA). The project’s goal is to develop a predictive decision
support Dashboard for Agricultural Water use and Nutrient management (DAWN) to sustain
food and energy crop production in the Corn Belt (https://dawn.umd.edu). The post-doctoral
associate will focus on the development, evaluation, and application of an advanced cropmodeling
system. This will involve calibrating, testing, and analyzing a suite of crop growth
models and coupling them with a regional climate model. The resulting coupled system will then
be used to generate more accurate seasonal forecasts of crop yields, carbon uptake, and nutrient
loading that can be shared directly with farmers. The associate will also be actively involved
with the overall project activities as part of an interdisciplinary team that includes research,
extension, and education specialists. Salary is commensurate with experience and University
benefits will be included.
Qualifications:
Applicants should have a Ph.D. (within 5 years) in agricultural, atmospheric or climate sciences,
and a strong background in crop dynamics and model development. They must have experience
and skill in programming (particularly Fortran and C) as well as analytical skill in model
evaluation and crop-climate interaction. Skills in parallel computing, machine learning, and GIS
application are desired and experience in mesoscale regional climate models encouraged. Strong
verbal and written English communication skills are required.
To apply:
Interested applicants should submit a cover letter, CV, and contact information for three
references to Professor Xin-Zhong Liang at xliang@umd.edu. The position is available
immediately, and applications will be reviewed on a rolling basis until the position is filled
modeling for a project funded by the United States Department of Agriculture (USDA)/National
Institute of Food and Agriculture (NIFA). The project’s goal is to develop a predictive decision
support Dashboard for Agricultural Water use and Nutrient management (DAWN) to sustain
food and energy crop production in the Corn Belt (https://dawn.umd.edu). The post-doctoral
associate will focus on the development, evaluation, and application of an advanced cropmodeling
system. This will involve calibrating, testing, and analyzing a suite of crop growth
models and coupling them with a regional climate model. The resulting coupled system will then
be used to generate more accurate seasonal forecasts of crop yields, carbon uptake, and nutrient
loading that can be shared directly with farmers. The associate will also be actively involved
with the overall project activities as part of an interdisciplinary team that includes research,
extension, and education specialists. Salary is commensurate with experience and University
benefits will be included.
Qualifications:
Applicants should have a Ph.D. (within 5 years) in agricultural, atmospheric or climate sciences,
and a strong background in crop dynamics and model development. They must have experience
and skill in programming (particularly Fortran and C) as well as analytical skill in model
evaluation and crop-climate interaction. Skills in parallel computing, machine learning, and GIS
application are desired and experience in mesoscale regional climate models encouraged. Strong
verbal and written English communication skills are required.
To apply:
Interested applicants should submit a cover letter, CV, and contact information for three
references to Professor Xin-Zhong Liang at xliang@umd.edu. The position is available
immediately, and applications will be reviewed on a rolling basis until the position is filled