The Alliance of Bioversity International and the International Center for Tropical Agriculture (CIAT) – a member of the CGIAR Consortium (www.cgiar.org) – delivers research-based solutions that harness agricultural biodiversity and sustainably transform food systems to improve people’s lives in a climate crisis (https://alliancebioversityciat.org).
The Alliance focuses on the nexus of agriculture, nutrition, and environment, working with local, national, and multinational partners across Africa, Asia, Latin America, and the Caribbean, and with the public and private sectors and civil society.
With novel partnerships, the Alliance generates evidence and mainstreams innovations to transform food systems and landscapes so that they sustain the planet, drive prosperity, and nourish people.
The Alliance of Bioversity International and CIAT has initiated a project, titled Artemis. The goal of Artemis is to develop a smartphone-deployable imagery-based phenotyping solution, built for applications in the global South, in breeding programs and on-farm trials, with potential applications across wider agricultural systems.
is a collaborative effort between the Alliance, the International Institute for Tropical Agriculture (IITA), Colorado State University, X ‘The Moonshot Factory’ of Google/Alphabet, and various national agricultural research organizations across the target countries.
The work will be focused on common beans, cowpeas, and sorghum cropping systems across Colombia, Senegal, Nigeria, and Tanzania.
As a result of the diverse nature of our work, this role will have the opportunity to work within a multicultural and multidisciplinary team, distributed across several countries around the world.
About the position
The Postdoctoral Fellow will lead and coordinate the analytical modeling component of the project, principally focused on breeding informatics and agricultural data science.
The position will analyze phenotypic variation within the project germplasm to develop breeding strategies for the target crops based on phenotypic selection.
A key element of the activities is to work with the various sources of phenomics data generated from the project, including traditional field observation-derived data and data generated by quantitative imagery models, to assess changes in selection accuracy and potential advancements in genetic gain from imagery-based approaches.
Additionally, the analytical framework will need to incorporate insights gained from on-farm evaluations of promising germplasm to identify resilient materials, leveraging ancillary environmental and crop management data to derive insights on the biophysical and/or agronomic mechanisms driving variety performance.
Analytical models will utilize existing breeding informatics software packages (e.g. AlphaSim) as well as develop custom approaches based on the project needs and objectives.
- Lead and coordinate the quantitative analytical activities across the project
- Develop analytical modeling frameworks to inform the breeding selection and varietal placement
- Automate routine analytical activities and contribute to capacity development of partners as needed
- Contribute to the organization and coordination of data collection and data systems processes
- Supervise and mentor supporting staff analysts and research assistants
- Stay up-to-date with the most recent literature on breeding informatics
- Contribute to project reporting
- Translate research findings into peer-reviewed publications
- Other tasks as assigned as relevant to expertise and ongoing or future projects
Qualifications and requirements:
- Ph.D. in informatics, statistics, data science, plant breeding, agronomy, plant physiology, ecology, or related fields
- Experience in predictive modeling and quantitative analysis with large datasets
- Experience in one or more of the following data science application areas: plant breeding, genomics, plant physiology, environmental analysis, spatial statistics, agroecology, and/or closely related areas
- Demonstrated professional practices in scientific programming (e.g., version control, ensuring reproducibility, documentation, open-access publishing of data, open-source publishing of code).
- Experienced in spatial analysis, integrating environmental covariate modeling is desired, but not required
- Substantial experience and demonstrated proficiency in scientific programming (using R and/or Python).
- Excellent level of professional English. Knowledge of other languages (e.g., Spanish, French, Swahili) is desirable, but not required.
- Proven scientific English writing skills
- Past experience in international agricultural research and working in Africa is desirable, but not required.
- Experience working on collaborative projects as part of an international team is desirable, but not required.
Terms of employment
This is an internationally recruited post-doctoral position and will be based in Arusha, Tanzania with opportunities to move to a hybrid remote-working environment. The position will report to the Project Leader, with co-supervision by the bean breeding program leads.
The initial contract will be for up to two (2) years, subject to a probation period of six (6) months, and is renewable depending on performance and availability of resources. This position is graded at level BG08 on a scale of 14 levels, BG14 being the highest level.
The Alliance of Bioversity International and CIAT offers a multicultural, collegial research environment with a competitive salary and excellent benefits. We are an equal opportunity employer, and strive for gender, diversity, and inclusion in our staff, without regard to race, color, religion, gender, gender identity, sexual orientation, national origin, ethnicity, age, disability, marital status, or any other characteristic.