DUTIES:
Manage and improve efficiency in maize breeding nurseries and field operations including screening germplasm for the key traits including drought, low nitrogen, heat, Striga, and fall armyworm resistance. This includes improvements in nursery and trial designs and field layouts to enhance accuracy
Manage crossing nurseries and new hybrid development from parental selection to advancement of hybrids to stages 1, 2 and 3. This includes breeder seed production to maintain genetic purity and ensure timely availability of seed to support partners
Manage Regional Variety Trials (RVT) and Multi-Environment Trials (MET) across locations to ensure standardized protocols, high-quality phenotyping, and data integrity. Apply advanced statistical methods (e.g., mixed models, G×E analysis) to guide selection and product placement decisions. The outcome is robust, data-driven advancement and deployment of superior hybrids
Support design and implementation of genomic selection (GS) and marker-assisted selection (MAS) strategies to enhance selection accuracy for complex traits. Integrate genomic prediction into early-stage evaluation and optimize training populations. The outcome is improved prediction accuracy and accelerated breeding progress
Manage and supervise field teams and technical staff, and support training of NARS partners in breeding methodologies, trial and nursery management, and digital data collection systems. The outcome is strengthened operational capacity and improved quality of data collection across sites
Contribute to scientific publications, and variety documentation. The outcome is effective communication of breeding progress and facilitation of product release
Perform other job-related duties as may be assigned by the supervisor
Requirements
QUALIFICATION:
MSc in Agricultural Science, Plant Science, Crop Science, Biotechnology, or related courses with a minimum of ten (10) years' performing a similar role in a well-structured environment. Experience in plant breeding is an added advantage.
COMPETENCIES:
The ideal candidate must:
Have strong analytical and quantitative skills with proficiency in R programing language statistical software (ASReml, BGLR, sommer).
Have high level of organization, attention to detail, and ability to work under multi-season, multi-location demands
Demonstrate ability to work collaboratively with national and international partners
Have solid understanding of breeding pipeline design, selection strategies, and genetic gain optimization
Have ability to interpret complex datasets and translate results into actionable breeding decisions.
Have project and team management skills, including coordination of multi-location trials and diverse teams
Have effective communication skills for reporting, stakeholder engagement, and scientific dissemination
Be experienced in digital breeding tools and data management systems