PhD Research Intern AI Memory & Personalized Education

7Edu Impact Academy•Cupertino, CA

16h•Remote

About The Position

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. The selected candidate will define how an AI system effectively retains, synthesizes, and utilizes long-term context from multiple perspectives to drive truly personalized education. We are building an advanced AI platform designed to facilitate long-term educational planning and decision-making across three key stakeholders: Students, Parents, and Teachers. This role combines theoretical framework design, applied AI prototyping, and empirical validation in a live product environment.

Requirements

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

Responsibilities

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