Apple Scholars in AI/ML

Please see the full solicitation for complete information about the funding opportunity. Below is a summary assembled by the Research & Innovation Office (RIO). Given Apple’s institutional limit of three nominees, each college or institute may nominate only two students as part of the internal competition.

Program Summary 

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.

Nominees should be pursuing research in one or more of the following research areas. The subtopics listed under each research area are not meant to be exhaustive or prescriptive, but rather highlight areas of particular interest to Apple.

Privacy Preserving Machine Learning

  • Federated Learning, Differential Privacy, Cryptographic Tools, Secure Multiparty Computation

Human Centered AI

Social Signal Processing, ML for Multimodal Interaction, ML Design and Human Factors, Usable ML Tools and Products, Interactive ML, Model Personalization, Human-in-the-loop ML

AI for Ethics and Fairness

  • Bias and Fairness in AI, Interpretable AI, Introspection, Robustness

AI for Accessibility

  • Accessible User Experiences, Automatic Personalization/Adaptation, interactions via New or Combined Modalities, Participatory Design with People with Disabilities

AI for Health and Wellness

  • ML and RL for Mobile Health, Time Series Representation Learning, Physiology- Informed Machine Learning, Modeling Multi-Modal Sensor Data, Causal modeling, Human behavior

ML Theory

  • Understanding ML, Generalization, Physics-based ML, Generative Models, Imbalanced Data Theory, Out-of-Distribution setting

ML Algorithms and Architectures

  • Auto ML, Model Compression, Architecture / Search, Optimization, Model Representation, Interpretability, Large-Scale ML, Imbalanced Data, Unsupervised and Self Supervised Representation Learning

Embodied ML

  • Imitation Learning, Multi-Output Models, Reinforcement Learning for Embodied ML, Hardware/Software Integration, Hardware Aware ML Training, Inference and Resource Constrained ML

Speech and Natural Language

  • Speech Recognition, Text to Speech, Conversational and Multi-Modal Interactions, Machine Translation, Language Modeling and Generation

Computer Vision

  • Semantic scene understanding, Video understanding , 3D scene understanding , Efficient Deep learning for computer vision, AI for content creation, Continual learning , Computer vision for AR/VR, Computer vision with Synthetic data , Language and vision, Computational photography, Vision for Robotics, Foundation model for industrial machine vision, Vision for industrial robotics

Information Retrieval, Ranking and Knowledge

  • Knowledge Extraction and Information Retrieval, Knowledge Inference, Large-Scale Graph Data Management, Machine Learning and Data Systems Integration, Search and Ranking

Data-Centric AI

  • Data efficacy, data efficiency, data generation, data fairness, synthetic data generation, dataset creation, data and annotation, Active learning, ML-enabled data annotation, augmentation and curation, Transfer learning with limited data, Unsupervised and weakly- supervised anomaly detection, Synthetic defect generation and simulation, Sim2real transfer learning,


CU Internal Deadline: 11:59pm MT August 15, 2022

Sponsor Application Deadline: September 28, 2022

Internal Application Requirements (all in PDF format)

  • Research Statement (5 pages maximum including citations): Please include past work and proposed direction for next 2 years clearly stating the hypothesis and expected contributions to the chosen research area.
  • Student Curriculum Vitae and Publication List

To access the online application, visit:


  • Nominee must be enrolled full time at the nominating university at the start of Fall 2023, and expect to be enrolled through the end of the 2023/2024 academic year
  • Nominee should be entering their last 2-3 years of study as of Fall 2023
  • Nominee must not hold another industry-sponsored full fellowship while they are an Apple Scholar in AI/ML (Fall 2023 to Summer 2025)

Limited Submission Guidelines

Invited institutions may nominate up to (3) PhD students pursuing research relevant to the research areas listed in the nomination guidelines. As such, each college or institute may nominate only two students as part of the internal competition.

Award Information

  • Gift amount covering full tuition and fees (enrollment fees, health insurance) for (2) academic years
  • $40,000 USD gift each year to help with living expenses and related expenses
  • $5,000 USD gift each year to support research-related travel and associated expenses