Ph.D. Scholar - Rapid Cycling and Predictive Breeding

About the role

The Ph.D. scholar will conduct research on rapid cycling and AI‑assisted breeding to improve efficiency, prediction accuracy, and genetic gain in dryland crops. The position is based in Kiboko, Kenya, and spans 3–4 years, subject to university registration and project funding.

Key responsibilities

• Develop and implement a research plan testing rapid cycling and predictive breeding hypotheses.
• Participate in field experiments comparing predicted and observed performance.
• Perform statistical and quantitative genetic analyses, including model evaluation and data visualization.
• Contribute to scientific manuscripts and conference presentations.

Required profile

• Master’s degree in Plant Breeding, Quantitative Genetics, Statistical Genomics, Crop Science or a related field.
• Strong interest in predictive breeding, rapid cycling, and applied breeding research.
• Ability to work collaboratively with scientists, breeders, and field teams.
• Enrollment or willingness to enroll in an African university with thesis work in Kiboko.

Required skills

• Proficiency in R for data analysis.
• Proficiency in Python for data analysis.

What we offer

• Support for tuition fees.
• Funding for research activities.
• Stipend according to CIMMYT Academy policies.