Summer Research program positions

The Summer 2026 Intern Application is Now Closed.

454 - PAL-ATA: Personalized Assistant for Learning

Project Name
PAL-ATA: Personalized Assistant for Learning

Project Description

In this research, we seek to prototype and study the effects of leveraging artificial intelligence to deliver personalized, interactive learning recommendations. The primary focus of this work is to expand the “content bottleneck” for adaptive systems, such that new content may be integrated and included into the system with minimal training.

The testbed for this work will be the Personal Assistant for Life-Long Learning (PAL3), which uses artificial intelligence to accelerate learning through just-in-time training and interventions that are tailored to an individual. The types of content that will be analyzed using machine learning and included in the system cover a wide range of domains. These include:

– Artificial Intelligence: Training on topics such as AI algorithms and emerging technologies that leverage AI and data science. Content on how to build, evaluate, and compare different AI systems for realistic use cases.

– Self-Regulated Learning: Training on transferable “learning to learn” skills for effective life-long learning. Target audience are learners studying for a high-stakes exams covering topics such as vocabulary, reading comprehension and basic mathematics. As students study core topics, self-regulated learning skills are introduced (e.g., setting and checking study pace, taking notes).

Job Description
The goal of the internship will be to expand the capabilities of the system to enhance learning and engagement. The specific tasks will be determined based on the status of the project at the time of the internship as well as your interests. Possible topics include work with: (1) Generative AI for Learning Content Creation or Analysis (e.g., multimedia: images, video, text, dynamic content), (2) Natural Language Processing or Dialog Systems for Coaching, (3) Learning Recommendation Systems, and (4) Content-specific technologies (e.g., artificial intelligence). Opportunities will be available to contribute to peer-reviewed publications.

Preferred Skills

Python, JavaScript/Node.js, R
Machine Learning Expertise, Basic AI Programming, or Statistics
Strong interest in machine learning approaches, intelligent agents, human and virtual behavior, and social cognition

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455 - AIRCOEE – AI Research Center of Excellence in Education

Project Name
AIRCOEE – AI Research Center of Excellence in Education

Project Description
The AIRCOEE initiative uses AI to teach AI and to help create content and training materials. It also has a curriculum revision tool and writing guide component. AIRCOEE also includes research on analyzing and supporting learning in groups, particularly by analyzing speech from multiple speakers in a small team or classroom to identify formation and leadership in ideas and critical thinking.

Job Description
Over the course of the summer, the intern will assist in development of software infrastructure, participate in AI-integrated content development, and informal testing of AI technologies for delivering or updating learning content. Intelligent and interactive content may include dialog systems, question / inquiry about passive content, as well as game-like learning scenarios (e.g., interactive simulations of AI algorithms). Platforms for this work include Python AI/ML libraries including generative AI tools such as OpenAI and LangChain, React Native, React JS, Node.js, and GraphQL. Interns involved in this project will be expected to document their designs, contributions, and analyses to contribute to related publications.

Preferred Skills

at least one AI course
Javascript/Typescript
Python, Python Notebook

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456 - Summer PhD Internship on Computing Minds for Artificial Intelligence

Project Name
Solving The Machine’s Problem of Other Minds

Project Description
The Social Simulation lab develops tools that give machines principled representations of our mental states. It is currently focused on models of social cognition (e.g., theory of mind) and judgment and decision making. Interns will develop projects within the bounds of theoretical models that the lab is developing. For example, the Theory of Mind Utility specifies how information access history can be engineered into representations of mental states. Its formalism makes specific predictions on how this will alter machine interpretation of human behavior relative to alternative approaches, such as Bayesian Theory of Mind. Another project, the Arena Model of human judgment, argues that humans select a judgment basis from an expansive set of judgment dimensions. Its formalism supports methods for AI systems to evaluate whether a given dimension is part of a person’s judgment basis during an episode.

Job Description
Summer interns work with the PI to identify a testable hypothesis related to the lab’s ongoing projects. The lab supports interns who want to work in formal methods, simulation, and behavioral experimentation. Note that behavioral experiments are constrained by current funding resources and IRB/HRPO application timelines.

Preferred Skills

Python for software and data science (R is also acceptable for data science)
Basic familiarity with cognitive psychology
Basic familiarity with AI systems

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457 - Research in Embodied Team AI

Project Name
Representations for Embodied Team AI

Project Description
The Human-Inspired Adaptive Teaming Systems (HATS) group at USC’s Institute for Creative Technologies invites applications for summer research internships. Our work on Embodied Team AI studies how teams of agents turn high-level intent into structured plans and build shared awareness from what each agent observes locally, drawing on multi-agent reinforcement learning, generative models, multimodal large language models, and graph-based representations. Interns join an active project and work closely with PhD students and research staff, with the goal of producing results that can contribute to a publication.

Job Description
The HATS group at USC ICT studies Embodied Team AI: how teams of agents coordinate in complex, partially observable environments. Our work combines multi-agent reinforcement learning, generative models, multimodal large language models, and graph-based representations, and is evaluated in simulation and game environments. Summer interns are paired with a PhD student mentor and meet regularly with lab researchers. The work involves implementing models, running experiments, and analyzing results, and concludes with a report & presentation to the lab. Where results support it, we aim for a workshop or conference submission.

Preferred Skills

Python & Pytorch
Generative Models
Multi-agent Reinforcement Learning

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Compensation: The base salary range for all intern positions is $1,254/week (undergrad). to $1,382/week (grad), paid at a monthly or hourly rate depending on employment type.
See FAQ’s for description of employment types | ICT Internship Personal Statment Template

USC is an equal opportunity, affirmative action employer. All qualified applicants will receive consideration for employment without regard to race, color, religion, sex, sexual orientation, gender identity, national origin, protected veteran status, disability, or any other characteristic protected by law or USC policy. USC will consider for employment all qualified applicants with criminal records in a manner consistent with applicable laws and regulations, including the Los Angeles County Fair Chance Ordinance for employers and the Fair Chance Initiative for Hiring Ordinance, and with due consideration for patient and student safety. Please refer to the Background Screening Policy Appendix D for specific employment screen implications for the position for which you are applying.