PhD Research Intern AI Memory Personalized Education

Benefits:

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

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EDU is an education technology organization dedicated to long-term academic planning and student development. For over a decade, we have supported K–12 learners through structured advising, college admissions strategy, and personalized mentorship, while building proprietary tools and frameworks to support scalable, data-informed guidance.

Our AI systems are designed to support longitudinal educational decision-making — integrating student progress, parental input, and instructional context to enable personalized, responsible, and evidence-based support.

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.

• 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.

• 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

Please email your application to: hiring team

Email Subject: AI Research Internship FULL NAME

Resume

A brief cover letter outlining your research interests regarding AI memory or user modeling.

A link to Google Scholar or an attachment of one relevant writing sample/paper.

Flexible work from home options available.