PhD Research Intern AI Memory & Personalized Education

About the role

We are seeking a PhD-level researcher for a 10–12 week summer internship focused on a critical technical and design challenge: Educational AI Memory.

Key Responsibilities

• Develop a theoretical framework for “Triangulated AI Memory” within an educational context.
• Collaborate with the engineering team to prototype memory architectures (e.g., RAG systems, vector stores, long-term context management) aligned with pedagogical objectives.
• Explore and formalize methods for representing evolving student, parent, and teacher perspectives within AI systems.
• Design and conduct qualitative and/or quantitative research to evaluate system utility, trust, and personalization effectiveness.
• Translate research concepts into actionable technical specifications.
• Contribute to a co-authored paper targeting top-tier venues (e.g., CHI, LAK, EDM, NeurIPS) based on the summer’s research.

Qualifications

• Currently enrolled in a PhD program in Computer Science, Human-Computer Interaction, Artificial Intelligence, Learning Sciences, or a related field, with a research focus in machine learning, memory architectures, user modeling, or human-centered AI.
• Strong track record of research in AI and machine learning.
• Demonstrated experience in User Modeling, Recommender Systems, Large Language Models (LLMs), or related areas.
• Solid understanding of the ethical, privacy, and design implications of AI in human-centered environments.
• Ability to translate theoretical research concepts into clear, actionable product and technical specifications.

Benefits

• 401(k) matching
• Flexible schedule
• Opportunity for advancement