Physical Address
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Dorchester Center, MA 02124
Deadline: July 31, 2025
The African Women in Agricultural Research and Development (AWARD) has launched the African Women in Data Science Fellowship 2025, a prestigious initiative aimed at equipping early to mid-career African women data scientists with advanced skills to drive agricultural transformation across the continent.
This fellowship is part of AWARD’s broader commitment to bridging gender gaps in science and leadership. The program focuses on strengthening the capacity of African women in data science to apply innovative digital and analytical tools to agricultural research, food systems, and policy development.
Fellows will engage in an immersive experience combining technical training, leadership development, and mentorship, making them key players in the digital future of agriculture in Africa.
Program Details
As a Fellow, you will engage in the following core activities:
- Participate in a 7-day, face-to-face women’s leadership course designed to strengthen your confidence, influence, and capacity to lead data-driven solutions (November 2025).
- Join a 2-week immersive in-person data science training course covering Python programming, machine learning, data wrangling, visualization, and statistical analysis (February 2026).
- Complete a 2-month virtual course focused on the application of data science tools to real-world challenges in agrifood systems and climate resilience (April – May 2026).
- Design and implement a data-driven capstone project addressing a practical issue in agriculture or climate. You will receive modest seed funding and technical guidance for project execution (February – September 2026).
- Undertake a competitive short-term institutional placement (1–3 months), known as Advanced Science Training (AST), within your home country. This placement provides an opportunity to apply your skills in a real-world setting and further deepen your technical expertise (May – September 2026).
- Receive ongoing guidance from senior data science professionals through structured mentoring relationships, including orientation, check-ins, and goal setting (March – November 2026).
- Participate in knowledge-sharing sessions, storytelling activities, and professional engagement opportunities through AWARD’s network (Throughout the fellowship).
SEE ALSO: Women in Africa (WIA) Young Leaders Programme 2025 for Young African Women Leaders
Eligibility Criteria
To apply, candidates must:
- Female citizens of one of the following countries: Benin, Côte d’Ivoire, Ethiopia,
Kenya, or Malawi. - Hold at least a Master’s degree in one of the following: Applied Statistics, Biostatistics,
Agricultural Engineering, Biosystems Engineering, Agricultural Economics, Data
Science, Bioinformatics or related disciplines. - Have 5 to 10 years of professional experience in a data-related role, ideally linked to
agriculture, climate, or development sectors. - Demonstrate intermediate proficiency in English (reading, writing, and speaking).
- Be committed to full participation in the 12-month program, including online and inperson activities.
- Resident in an African country throughout the Fellowship period
- Is not a selected Fellow for any other Fellowships offered by AWARD
- The program targets African women from Benin, Côte d’Ivoire, Ethiopia, Kenya, and Malawi with demonstrated experience in data-related roles and a commitment to applying data for development. Fellows will be drawn from diverse sectors, including government, academia, research, civil society, development agencies, and the private sector.
Application Process and Documents Required
- Key Components Assessed
- Technical proficiency: demonstrated application of data science tools and reasoning
- Motivation and career goals: alignment with the Fellowship objectives
- Use-Case proposal: relevance, feasibility, and potential impact
- Practical data exercise: ability to interpret data and communicate insights
Contact and Support
For questions about the application or the Fellowship, please send an email to
awardinfo@cifor-icraf.org
