Ph.D. Scholar - Rapid Cycling and Predictive Breeding

CIMMYT is a cutting edge, non-profit, international organization dedicated to solving tomorrow's problems today. It is entrusted with fostering improved quantity, quality, and dependability of production systems and basic cereals such as maize, wheat, triticale, sorghum, millets, and associated crops through applied agricultural science, particularly in the Global South, through building strong partnerships. This combination enhances the livelihood trajectories and resilience of millions of resource-poor farmers, while working towards a more productive, inclusive, and resilient agrifood system within planetary boundaries.For more information, visit https://www.cimmyt.org/.CIMMYT is implementing a project to enhance the speed and precision of dryland crop breeding through artificial intelligence, genomic prediction, rapid generation advancement, and rapid cycling genomic selection (RCGS). The project aims to radically shorten breeding cycles, increase genetic gain, and improve the delivery of climate-resilient, market-preferred varieties for dryland farming systems.A key part of the project focuses on testing rapid cycling schemes such as recycling at very early generations (F1) and using haplotype-based cross prediction to select individuals to generate succeeding cycles. The project also emphasizes learning loops, where early-generation predictions are compared with conventional fixed line predictions and realized field performance to refine breeding decisions and improve future cycles.The Ph.D. scholar will generate research evidence on whether rapid cycling and AI-assisted breeding improve breeding efficiency, prediction accuracy, and genetic gain in dryland crops. The research will focus on testing hypotheses related to recurrent selection, F1-based rapid cycling, sparse testing, and the translation of genomic predictions into realized field performance.This position will be based at Kiboko,...