Apply for the Women in AI Fellowship
The Health Pulse · Fellowship, FL · 3 days ago
AnalystFull-time
About the role
The Artificial Intelligence (AI) and Machine Learning (ML) fellowship is designed to strengthen women’s leadership in computational research, expand access to AI/ML expertise, and support doctoral work that applies machine learning to real-world social, scientific, and development challenges.
Overview
This fellowship is ideal for women who want to advance computational research, strengthen their technical skills, and contribute to impactful AI-driven solutions.
Funding
USD 5,000. One-time grant that may be used for:
- Tuition or academic fees
- Computing resources
- Data acquisition or analysis
- Mentorship support for AI/ML
- Fieldwork or research-related travel
- Technical AI/ML collaboration via KAIA Network.
Fellowship Benefits
- Structural technical support, including:
- Matching each fellow with an AI/ML collaborator through the KAIA Network
- Access to a growing community of AI engineers, data scientists, and interdisciplinary researchers
- Capacity-building seminars and virtual workshops
- Optional technical training modules
- Increased visibility for the fellow’s research
- Membership in a global community of women AI/ML researchers
- Opportunity to present research through KAIA-hosted seminars
- Interdisciplinary knowledge exchange sessions
- Networking with partners such as UN agencies, universities, and civil society organizations
- Knowledge Dissemination and Impact Expectations
Qualification
- Currently enrolled in, or admitted to, a PhD program at an accredited institution in Sub-Saharan Africa
- Conducting research in any social science or related discipline, including Computer science, Engineering, Economics, Public health, Environmental science, Socialogy, Demography, Development studies
- Demonstrating a clear intention to integrate AI/ML methodologies into their doctoral research
- Willing to participate actively in the KAIA community
How to apply
Apply here
For more information, visit the official KAIA webpage here