Postdoctoral Research Fellow in Crop Quantitative Genetics
Core
Develop and apply advanced quantitative genetics methods to improve genomic prediction of complex traits in soybean and refine methodologies for predictive breeding.
Role type
Postdoctoral Research Fellow in Crop Quantitative Genetics
Builds
Genomic prediction models for crop yield and related traits
Domain
Agriculture + Plant Genomics
Deliverable
production ML models
Required skills
Mixed-model statistical methodology, Genomic prediction, Crop simulation, Machine learning, Hierarchical modelling, Statistical analysis of large multidimensional datasets
Preferred skills
Publishing in refereed journals, External research funding applications, Collaborative research engagement
Technologies
Mixed models, Genomic prediction, Crop simulation, Machine learning
Responsibilities
Conduct univariate and multivariate statistical analyses of crop datasets; Develop and apply mixed-model statistical methodology; Assist with mentoring students and publish scholarly research
Seniority
Postdoctoral, hands-on IC