The Apple Scholars in AI/ML PhD fellowship program recognizes the contributions of emerging leaders in computer science and engineering at the graduate and postgraduate level. The PhD fellowship in AI/ML was created as part of the Apple Scholars program to support the work of outstanding PhD students from around the world, who are pursuing cutting edge research in machine learning and artificial intelligence.
Duke may nominate up to (3) students. Universities may nominate a maximum of (1) student to any of the research areas (see below).
Guidelines will be released in June. The password to access the guidelines will be available by request. Duke students interested in this opportunity can contact fundopps@duke.edu.
Deadlines:
- Duke Internal Deadline: July 8, 2024
- Deadline for Nominations: Sep. 10, 2024
Each university may nominate up to (3) students. Universities may nominate a maximum of (1) student to any of the following research areas:
- Privacy Preserving Machine Learning
- Human Centered AI
- AI for Ethics and Fairness
- AI for Accessibility
- AI for Health and Wellness
- ML Theory
- ML Algorithms and Architectures
- Embodied ML
- Speech and Natural Language
- Computer Vision
- Information Retrieval and Knowledge
- Data-Centric AI
Nominees must meet the following criteria to be considered:
• Nominee must be enrolled full time at the nominating university at the start of Fall 2025, and expect to be enrolled through the end of the 2025/2026 academic year
• Nominee should be entering their last 2-3 years of study as of Fall 2025
• Nominee must not hold another industry-sponsored full fellowship while they are an Apple Scholar in AI/ML (Fall 2025 to Summer 2027)
Owing to the sponsor's restriction on the number of applications that may be submitted from Duke, anyone wishing to pursue nomination should submit the following materials as one PDF:
• CV and publication list
• A one-page abstract describing your innovative research, your record as thought leaders and collaborators in your fields, and your unique commitment to take risks and push the envelope in machine learning and AI.
Please submit internal materials through My Research Proposal. (Code: ILN) https://www.grantinterface.com/sl/HQShLh
Instructions for creating an account (if needed) and submitting your materials: https://ctsi.duke.edu/about-myresearchproposal