PhD Research Intern AI Memory & Personalized Education

 Posted 3 months ago
     
5-10 years experience
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AI Summary

The role involves designing a theoretical framework for 'Triangulated AI Memory' and collaborating on prototyping memory architectures like RAG systems aligned with pedagogical goals. The intern will also design and conduct validation studies and contribute to a co-authored publication.
Benefits:
  • 401(k) matching
  • Flexible schedule
  • Opportunity for advancement
About 7EDU

7EDU 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.

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. 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.

Key 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.

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

Please email your application to: hiringteam@7edu.org 

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.

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