Maize Breeder

Responsibilities

• Drive breakthrough breeding advancements using machine learning, genomic prediction, and GxE interaction tools.
• Implement breeding pipelines incorporating MAS, genomic selection, haplotype tracking, and high-throughput phenotyping.
• Develop breeder-focused dashboards and translate high-dimensional data into intuitive visuals for strategic decision-making.
• Integrate physiological traits and agronomic management into predictive ML-based models.
• Mentor early-career scientists and build institutional capacity through partnerships with NARES, SMEs, and universities.
• Publish research in top-tier journals and contribute to large-scale resource mobilization proposals.

Requirements

• PhD in Plant Breeding, Genetics, Genomics, Data-Enabled Crop Improvement, or a closely related discipline.
• Minimum 2 years of post-PhD experience in maize breeding or related crop improvement for tropical environments.
• Demonstrated success in deploying molecular and genomic tools within operational breeding pipelines.
• Advanced understanding of quantitative genetics, including MAS, GS, genomic prediction, and QTL discovery.
• Proficiency in data analysis software such as R, SAS, or Genstat.
• Strong experience in collaborating across disciplines, including genomics, pathology, and data science.

Preferred Qualifications

• Practical knowledge of machine learning algorithms for parent selection and performance prediction.
• Experience with breeding informatics and database design.
• Proven track record of leadership in technical innovation and program strategy.

Benefits

• Internationally competitive salary.
• Housing allowance and car.
• Comprehensive health and life insurance.
• Assistance for children’s education.
• Paid vacation and annual home travel airfare.
• Retirement plan contributions and relocation assistance.

About the Company

CIMMYT is a cutting-edge, non-profit, international organization dedicated to solving global food security challenges. We focus on improving the quantity, quality, and dependability of production systems for essential cereals like maize and wheat through applied agricultural science and strong global partnerships.