Post‐Doctoral Researcher position on Soybean Multi‐model Comparison and Improvement

Employer: University of Kentucky

Position Type: Funded

Location: Lexington KY

Comments:

Location: University of Kentucky, Lexington, KY. This research is part of an international
collaboration across researchers within the Agricultural Model Intercomparison and
Improvement Project (AgMIP; http://www.agmip.org/).

Appointment and start date: To be appointed starting on December 1, 2018 (or as soon as
possible thereafter). This position is for one year and could be extended pending on additional
funding.

Project description: Crop model responses to the effect of CO2, temperature, water, and
nitrogen (CTWN) introduce large uncertainty when predicting future crop production. Testing
and developing improved crop models that can predict across this range of environmental
conditions involves major collaborative efforts between field experimentalists, crop
physiologists, crop modelers, and climatologists. We are seeking a highly motivated individual
that will work with an international team of crop modelers and data experimentalists. The
candidate will lead the data analysis and generation of research manuscripts on soybean crop
model comparison and improvement on CTWN sensitivity (Phase I) and on model testing with
experimental data from FACE and eddy‐covariance towers data (Phase II). The candidate will
work closely with a multi‐disciplinary mentoring team with extensive experience in model
evaluation and improvement. This project will be the first international multi‐model
comparison done on a major legume crop.

Responsibilities: Preparation of model inputs, evaluation of model outputs, coordination of
modeling activities within the AgMIP‐Soybean team, writing research manuscripts.
Qualifications: PhD in crop modeling or in grain crops ecophysiology or agronomy with
experience in the use of a crop simulation model. Skilled knowledge of statistical analysis
software and coding language.

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

  • Cover letter
  • Curriculum vita with at least two references

Post-Doctoral Researcher in Soybean Physiology and Modeling of Plant Nitrogen Cycling

Employer: University of Kentucky

Position Type: Funded

Location: Lexington KY

Comments:

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.

Responsibilities

  • 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.

Qualifications

  • 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