Help shape African AI research while learning how to review papers

As part of our mission to strengthen the African AI research ecosystem, the Deep Learning Indaba is excited to announce a Call for Mentored Reviewers. We are inviting Master’s students and early-stage PhD students based in or from Africa to apply to be mentored reviewers for the Indaba 2025 research track.

This is a unique opportunity to:

Learn How to Review Research Papers

Selected mentored reviewers will be paired with experienced, senior reviewers and will collaboratively review submissions to the Indaba 2025 Call for Papers. You’ll gain hands-on experience in academic peer review, learning how to critically assess technical work, write constructive feedback, and contribute to the research community.

Mentorship and Training

This program is offered in collaboration with the Indaba Mentorship Team. Reviewers will receive:

  • Guidance and oversight from experienced reviewers
  • A brief training on how to write effective and fair reviews
  • Feedback on their review quality
  • Recognition of their contributions

Eligibility

  • You are a Master’s student or early-stage PhD student in AI, machine learning, data science, or a related field
  • You are based in Africa or are of African nationality studying abroad
  • You have some research exposure (e.g., completed a Master’s thesis, co-authored a paper, attended workshops)
  • You are excited to learn and contribute to the peer review process

Timeline

  • Applications close: 20th April 
  • Reviewer training: 9th May 
  • Review period: 1st June to 15th June 
  • Time commitment: 2–3 papers, reviewed in collaboration with a mentor

Why Join?

  • Develop reviewing skills that will help you as a researcher
  • Get a behind-the-scenes look at the publication process
  • Contribute to building a strong African research ecosystem
  • Receive a certificate of participation and acknowledgment on the Indaba website

Apply to be a Mentored Reviewer now !

Deadline: 20th April 

If you have any questions, contact us at: publications@deeplearningindaba.com