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Women in AI/ML Doctoral Fellowship 2026: Empowering the Next Generation of Women Leaders in Artificial Intelligence

Artificial intelligence and machine learning continue to reshape global systems — from health and climate to economics, governance, and public policy. Yet despite the transformative power of these technologies, women remain significantly underrepresented in advanced AI/ML research and leadership roles. The Women in Artificial Intelligence and Machine Learning (AI/ML) Doctoral Fellowship directly addresses this gap […]

查看原始信息 · Opportunities for Youth
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全球
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博士, 专业人士
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博士
专业人士

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申请要求

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8 任务
  • Email address
  • Full name
  • Gender identity
  • Country of citizenship
  • Country where their PhD institution is located
  • Current doctoral status
  • Name of accredited PhD institution
  • Confirmation of AI/ML integration in their research

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关于机会

Artificial intelligence and machine learning continue to reshape global systems — from health and climate to economics, governance, and public policy. Yet despite the transformative power of these technologies, women remain significantly underrepresented in advanced AI/ML research and leadership roles. The Women in Artificial Intelligence and Machine Learning (AI/ML) Doctoral Fellowship directly addresses this gap […]

Artificial intelligence and machine learning continue to reshape global systems — from health and climate to economics, governance, and public policy. Yet despite the transformative power of these technologies, women remain significantly underrepresented in advanced AI/ML research and leadership roles. The Women in Artificial Intelligence and Machine Learning (AI/ML) Doctoral Fellowship directly addresses this gap by providing financial support, mentorship, technical collaboration, and global visibility to women PhD scholars across Sub‑Saharan Africa.

This 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. It is a unique opportunity for emerging women researchers to join a global network, access cutting-edge resources, and contribute to ethical, inclusive AI innovation.

About the Fellowship

The Women in AI/ML Doctoral Fellowship supports outstanding women PhD candidates whose research integrates artificial intelligence or machine learning methodologies within the social sciences or related fields. The program is hosted in partnership with The New School and the KAIA Network, ensuring that fellows are embedded in a vibrant interdisciplinary ecosystem of AI engineers, data scientists, and social scientists.

The fellowship aims to:

  • Expand women’s participation in advanced AI/ML research
  • Strengthen interdisciplinary collaboration
  • Support research that applies AI/ML to societal impact
  • Build a global community of women leaders in AI

Applicants must create a KAIA Network profile and submit their application through the platform to be considered.

Who Should Apply

The fellowship is open to women who meet the following criteria:

  • 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
    • sociology
    • demography
    • development studies
  • Demonstrating a clear intention to integrate AI/ML methodologies into their doctoral research
  • Willing to participate actively in the KAIA Network community

This fellowship is ideal for women who want to advance computational research, strengthen their technical skills, and contribute to impactful AI-driven solutions.

What the Fellowship Provides

1. Research Funding — USD 5,000

A one-time grant that may be used for:

  • Tuition or academic fees
  • Computing resources
  • Data acquisition or analysis
  • Mentorship support for AI/ML integration
  • Fieldwork or research-related travel

This funding is designed to remove financial barriers and accelerate the fellow’s research progress.

2. Technical AI/ML Collaboration via the KAIA Network

The fellowship provides structured 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

This ensures that fellows receive hands-on technical guidance and become part of a global AI research ecosystem.

3. Professional Development and Networking

Fellows will benefit from:

  • Membership in a global community of women AI/ML researchers
  • Opportunities to present research through KAIA-hosted seminars
  • Interdisciplinary knowledge exchange sessions
  • Networking with partners such as UN agencies, universities, and civil society organizations

These opportunities help fellows build long-term professional relationships and expand their research impact.

4. Knowledge Dissemination and Impact Expectations

Each fellow is expected to:

  • Produce at least one open-access research output, such as:
    • Working paper
    • Dataset
    • Software package
    • Technical report
  • Publish a reflective blog post on the KAIA Network
  • Share research findings through a KAIA-hosted seminar or webinar

These outputs ensure that the fellowship contributes to global knowledge and supports open, inclusive AI research.

Application Requirements

Applicants will be asked to provide:

  • Email address
  • Full name
  • Gender identity
  • Country of citizenship
  • Country where their PhD institution is located
  • Current doctoral status
  • Name of accredited PhD institution
  • Confirmation of AI/ML integration in their research

All applications must be submitted through the KAIA Network platform.

Deadline

Applications close on July 31, 2026. Late submissions will not be accepted.

 

For more information about this opportunity and to apply visit here

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