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ETS Internship, Fellowship and Visiting Scholar Programs in Research

Collaborate with ETS researchers to carry out innovative and impactful R&D projects.

Learn more about available internships and how to apply.


ETS® AI Labs™ 2023 Summer Internship Program


The ETS® AI Labs™ work drives the innovation and development of teaching and learning technologies that are grounded in research and powered by next-generation AI. The Labs are dedicated to working closely with end-users to uncover real-world needs, and co-designing and prototyping solutions to meet those needs. Our staff is made up of scientists (impact research, learning and data), software developers, engineers (AI and research), user experience researchers and designers, instructional designers, scrum coordinators, and product owners.

If you’re accepted into the ETS AI Labs summer program, you’ll participate in user needs, discovery and exploration, solution ideation and validation, capability and prototype development, iterative user validation and data-driven solution optimization.

We work in agile development teams to apply the best of foundational learning and cognitive science to the design, development and testing of solutions to meet educator and learner needs. Upon the completion of the program, you’ll have the opportunity to present your findings to teams across R&D.



You’ll conduct user-inspired research and development leading to the production of technology enhanced learning solutions. Depending on which project you are selected for, you may participate in any number of research and development activities, such as:

  • user needs analysis and validation
  • solution ideation
  • wireframing and prototyping
  • user experience research and design
  • back- and front-end prototype development
  • user testing and iteration
  • effectiveness efficacy studies

You will create and give presentations about your project at the end of the internship period.

Areas of expertise

You’d be a great fit for this program if you have interest and expertise in the following:

  • learning or cognitive science
  • software development
  • AI and ML engineering
  • user experience research and/or design
  • instructional design
  • product ownership
  • impact research science

Eligibility requirements

  • Completion of bachelor's degree
  • Actively enrolled or accepted into a graduate program aligned to a Lab focus (students who have deferred enrollment due to extenuating circumstances will be considered)

In a given year, you may apply to only one of the RMS, ETS AI Labs or NAEP internship programs. Please apply to the internship program that best fits with your qualifications and research interests.


The main criteria for selection will be the match of your interests and experience with the focus of the Labs.

ETS affirmative action goals will be considered. The ETS AI Labs value building teams of individuals from diverse backgrounds and with diverse experiences. We strongly encourage students from underrepresented groups and backgrounds to apply. Late or incomplete applications will not be considered.

Complete the electronic application form. On the application form:

  1. Identify the research areas you are interested in and provide a written statement about your interest in the areas and how your education and experience align with the work of the areas.
  2. Attach a copy of your curriculum vitae (preferably as a PDF).
  3. If you are (or have been) actively enrolled in a graduate program attach a copy of your graduate transcripts (unofficial copies are acceptable).
  4. If you were accepted into a graduate program and deferred enrollment, attach proof of acceptance.
  5. Download the recommendation form and share it with your recommenders. The link to the recommendation form is on the application. (You can download the form prior to completing the application.)
    • Recommendations should come from an academic advisor, a professor who is familiar with your work as it relates to the project of interest, or an individual who you have worked with on a closely aligned project. 
    • ETS will only accept two recommendation forms.
    • Recommendations should be sent electronically to and must be received by January 1, 2023.

Dates and location

  • Deadline: The application deadline is January 1, 2023
  • Decisions: You’ll be notified of selection decisions by March 31, 2023
  • Duration: 10 weeks: June 5, 2023–August 11, 2023


  • $15,000 stipend
  • You will visit the ETS Princeton campus, expenses covered, two times:
    • First week of program
    • Last week of program

About the ETS AI Labs

The Labs aim to advance educational and employment opportunity by providing tools and services that help individuals worldwide identify, efficiently progress toward, and meet their learning and career goals.

Labs teams leverage NLP and AI capability to deliver personalized solutions to educators and learners in the K–12, higher education and workforce spaces. The solutions we develop enable efficiencies, flexibility and actionable insights.

The AI Research Lab teams are agile and change with data-driven learning, as well as corporate strategies. Our teams primarily focus on:

  • Language Learning
  • K–12 — Educators and Students
  • Higher Education — Educators and Students
  • Workplace — Employers and Employees

Our teams construct automated environments that enable targeted learning pathways, individualized supports for learners, and coursewide recommendations for educators. The teams develop adaptation capabilities based on rigorous models and actionable insights to support decision making among learners and educators.

If you have a background in data science, learning science, cognitive science, instructional design, user experience research and design, or software development, you’ll benefit from an internship on one of these teams.

Possible projects

  • AI and adaptivity projects that offer the opportunity for you to think through how an assessment for learning model might be constructed, meet with users to understand what activities would support the learning model and create user data footprints required to enable an adaptive experience.
  • Insights and intervention projects that offer you the opportunity to think about and develop principles for ingesting, storing, and analyzing data and using the data to reveal actionable insights and recommended interventions to educators and learners.
  • Predicting outcomes through usage data projects involve thinking through the user progressions within a system, understanding where important user interactions are, and aligning both with what data are captured/available in the system.

The automated scoring teams develop capabilities that enable automation in scoring of language assessments; learning and tool development; and engines that support recommendations and interventions. These teams prioritize responsible application of AI and expand on our AI scoring thought leadership in adjacent areas.

If you have a background in data science, computer science, natural language processing, machine learning and/or deep learning, you’ll benefit from an internship in the AI Research Lab.

Possible projects

  • Automated scoring projects offer you the opportunity to apply Natural Language Processing or AI methods to written and spoken formative assessments to provide meaningful insights to educators and learners.
  • Real-time targeted speaking feedback projects include the use of NLP and AI methods paired with theoretical research and user feedback to understand the features that are most important for users to receive feedback on and how to reveal those features to users.

Our agile teams develop prototypes to support the establishment of an ecosystem of interconnected language learning and assessment systems that provide personalized and ongoing support for language learners domestically and throughout the world.

Students with a background in data science, learning science, cognitive science, linguistics, software engineering, software development, computer science, instructional design, or user experience research and design would benefit from an internship one of these teams.

Possible projects

  • Promoting proficiency through meaningful feedback projects involve understanding user needs, consultation with the language learning literature for insights into how best to meet those needs, and the application of data gathered from both to the development of prototypes of meaningful interpretation layers of speech scoring data.
  • Supporting fluency by practicing confidently projects involve collecting and analyzing user feedback, conducting analyses of beta tester usage data within the app, and making concrete recommendations for optimization of existing features and/or development of new features in the app.
  • Meeting the needs of young English-language learners projects involve the ideation, design, and development of capabilities, product concepts, and prototypes that support young learners as they enter and progress in their language learning journey.


For more information, contact us via email.