University of Kentucky
Location of Position (City): 
Location of Position (State): 
Removal Date: 
Friday, October 1, 2021

Location: University of Kentucky, Lexington, KY. This is a project in collaboration with University of Arkansas and University of Minnesota funded by the United Soybean Board.

Appointment and start date: To be appointed starting on January 1, 2019 (or as soon as possible thereafter). This position is for one year and could be extended pending on additional funding.

Project description:  Seed protein concentration is often reduced in modern soybean cultivars as well as under conditions of high yield potential. Identifying management practices that can increase both soybean productivity and seed quality while minimizing N losses and ensuring the sustainability of grain cropping systems requires the combination of field experimental trials with process-based models capable of predicting these interactions. The Post-Doctoral candidate will be part of an interdisciplinary team that studies the interactive effects of environment, genotype, and N availability on the physiological processes determining yield and seed composition. Field experiments quantifying the effect of late-season cultural practices (N fertilizer applications and B. japonicum inoculations) on the fraction of biological N2 fixation, seed N accumulation, protein concentration, and amino acid profiles will be conducted across three different states with contrasting environmental conditions (Arkansas, Kentucky, Minnesota). The data collected will be used to test and improve plant processes influencing seed N accumulation and final protein concentration in a process-based soybean crop model.


  • Coordination of the data collection at three locations, data analysis, and interpretation of agronomic, physiological, and seed composition data. 
  • The candidate will lead the efforts of model parametrization, evaluation, and improvement of DSSAT-CROPGRO-Soybean for prediction of seed N accumulation and final protein concentration.
  • Preparation of research manuscript(s) that identify management practices that may be employed to improve crop productivity and seed quality in soybean grown in different environments.


  • PhD in grain crops ecophysiology, agronomy, crop modeling or related discipline is required.
  • Previous experience with process-based crop models and supported by publications is desirable. Experience using the DSSAT-CROPGRO software is preferred, but not required.
  • Knowledge of statistical analysis (i.e. SAS, R software) is required.
  • Knowledge of coding languages such as R and Fortran is desirable.

Application: Please submit to Dr. Montse Salmeron (msalmeron@uky.edu) the following documents:

  • Cover letter
  • Curriculum vita with at least two references
Position Type: