Ph.D. Scholar - Rapid Cycling and Predictive Breeding
On-siteKiboko, Makueni County, Kenya
Job Summary
Develop and implement a Ph.D. research plan evaluating rapid cycling and AI-assisted breeding efficiency in dryland crops. Conduct hands-on field research comparing predicted genomic performance with observed outcomes to validate selection pipelines. Perform statistical and quantitative genetic analyses for model evaluation, data visualization, and interpretation of results. Lead or contribute to scientific manuscripts suitable for peer-reviewed publication and presentations. This position is based at Kiboko, Kenya, with a duration of 3–4 years subject to university registration and project funding. The scholar will be supervised by a CIMMYT scientist and a university academic supervisor, working closely with project staff on RCGS validation and pipeline implementation. Successful candidates will defend a Ph.D. thesis and produce at least two peer-reviewed publications.
Required Qualifications
- Master's degree in Plant Breeding, Quantitative Genetics, Statistical Genomics, Crop Science, or a closely related field
- Ability to analyze data using R and/or Python
- Good writing, analytical, and problem-solving skills
- Ability to work collaboratively with scientists, breeders, and field teams
- Applicant should be enrolled or agree to enroll in a university in Africa, with thesis work in Kiboko, Kenya, and with opportunities to travel to project scope countries (Ethiopia, Tanzania)
- Good command of the English language
Desired Qualifications
- Strong interest in predictive breeding, rapid cycling, and applied breeding research
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