ILRI Research Fellow - Developing Climate-Smart Forages for Resilient Livestock Systems in East Africa

International Livestock Research Institute (ILRI) seeks to recruit a Research Fellow under the supervision of the Forage Genebank team within the Livestock Genetics, Nutrition and Feed Resources Program.

ILRI works to improve food and nutritional security and reduce poverty in developing countries through research for efficient, safe and sustainable use of livestock. It is the only one of 15 CGIAR Research Centres dedicated entirely to animal agriculture research for the developing world. Co-hosted by Kenya and Ethiopia, it has regional or country offices and projects in East, South and Southeast Asia as well as Central, East, Southern and West Africa. www.ilri.org

The Forage Genebank at ILRI holds a diverse collection of tropical and subtropical forage accessions and related information. The genebank conserves nearly19,000 accessions from over 1,800 species. The collection is one of the most diverse collections of forage grasses, legumes and fodder trees held in any genebank in the world.  In addition to the routine genebank operations, the genebank also conducts characterization at agronomic, nutritional and genomic levels and add value to the collection through generating information and making available the seeds of the accessions to diverse users. https://www.ilri.org/research/facilities/ilri-genebank .

Advances in high-throughput sequencing technologies such as Whole Genome Sequencing (WGS) and Genotyping-by-Sequencing (GBS) have generated large volumes of genomic data that offer significant opportunities for accelerating breeding and genetic improvement programs. However, the increasing scale and complexity of these datasets require advanced bioinformatics expertise, robust analytical workflows, and strong data management systems to fully harness their potential.

Within the current research program, substantial genomic datasets have been generated from diverse forage germplasms. There is a critical need to systematically analyze, curate, and translate these data into actionable insights that support publication outputs, breeding decisions, and capacity development. In addition, strengthening institutional capacity in bioinformatics and statistical genomics is essential to ensure long-term sustainability and local expertise development.

The fellowship will focus on advanced genomic data analysis, interpretation, and capacity building. The Fellow will support the processing and analysis of WGS and GBS datasets, contribute to scientific publications, and enhance institutional capacity through training and mentorship in bioinformatics tools and programming (e.g., R, Linux, Python). The position is designed to bridge analytical gaps, strengthen research outputs, and support evidence-based breeding and genetic research initiatives.

1. → Genomic Data Analysis and Reporting
   • →Analyze and summarize Whole Genome Sequencing (WGS) and Genotyping-by-Sequencing (GBS) datasets.
   • →Generate high-quality tables, figures, and summary statistics suitable for peer-reviewed publications and technical reports.
   • →Contribute to manuscript preparation, including methods, results interpretation, and supplementary materials.
2. → Field and Experimental Data Collection
   • →Actively participate in field and/or laboratory data collection activities.
   • →Ensure proper data recording, quality control, and adherence to established research protocols.
3. → Capacity Building and Training
   • →Provide hands-on training to students and junior researchers in R programming and bioinformatics workflows.
   • →Develop training materials (scripts, tutorials, example datasets) to support sustainable capacity development.
   • →Offer mentorship in genomic data analysis, visualization, and reproducible research practices.

The ideal candidate should possess the following:

1. Education
   • MSc degree in Bioinformatics, Genetics, Genomics, Computational Biology, Statistics, Data Science, or a related field.
2. Technical Expertise
   • Demonstrated experience in handling and analyzing large-scale datasets (e.g., WGS, GBS, or other high-throughput sequencing data).
   • Strong proficiency in R, Linux/Unix environments, and Python.
   • Experience with bioinformatics pipelines, genomic data processing tools, and reproducible workflows.
   • Familiarity with HPC environments and version control systems (e.g., Git) is an added advantage.
3. Analytical and Research Skills
   • Ability to generate publication-quality tables, figures, and statistical analyses.
   • Experience contributing to peer-reviewed publications is desirable.
4. Additional Competencies
   • Strong problem-solving skills and attention to detail.
   • Ability to train and mentor students or junior researchers.
   • Good written and verbal communication skills in English.
5. Must be a staff member of a National Agricultural Research Institute or organization.