Applied Research Lead, AI for Teaching

About the lab

The EduNLP Lab at Stanford develops natural language processing methods and tools that support equitable, student-centered teaching. We build measures of what teachers and students say and do, such as how students reason aloud in small groups, how teachers respond to student ideas, and how teachers adapt curriculum. We use those measures both as research outcomes and as feedback teachers can act on. Our work has been deployed and tested at scale with edtech partners; for example, automated feedback on teachers’ questioning, delivered through a partner product, improved questioning quality in brick-and-mortar classrooms.

This position is part of Teacher CoPilots II, a multi-year research program in partnership with the AI Teaching Assistant strand of Stanford SCALE’s AI Hub for Education. The program studies where and how much AI support strengthens teachers’ decision-making while preserving their skill, and releases measures, benchmarks, evaluators, and protocols as public goods.

About the role

Research has the most impact when it reaches the products teachers use, and studying those products in real classrooms produces some of the most informative research. This role sits at that intersection. You will work with edtech partners, such as Coteach and Amplify, to bring the lab’s measures, evaluators, and feature concepts into their products; design and run the studies that test them; and publish what you learn. You will also help us study the translation process itself: what it takes for research tools to become product features that scale sustainably.

You will work closely with the lab’s project manager, who leads our educator and district partnerships, and with technical staff, postdocs, and graduate students who build and validate models. You do not need to be a machine learning engineer, but you do need to be fluent enough to work directly with data and with partners’ engineering teams.

Position Summary

Partner-embedded research

• Scope joint projects with edtech partners, matching each one to a research question and a feasible study.
• Balancing between different pacing, metrics, and level of agility across stakeholders
• Translate between product and research needs: turn research measures into specifications, evaluation harnesses, or prototypes that product teams can integrate, and turn product questions into testable designs.
• Lead multidisciplinary teams that span the lab and partners’ product and engineering teams.

• Build and maintain data pipelines from data use agreements to transfer, storage, and organization of data.

Study design, analysis, and writing

• Collaborate with the principal investigator to design the research approach for each partner study, and integrate results across studies.
• Design experiments in settings with few precedents, such as in-product A/B tests and randomized or quasi-experimental studies, including power analyses and preregistration.
• Independently select approaches for developing, testing, and evaluating new methods, including LLM-based evaluators and measures used inside products.
• Analyze outcomes for teacher practice and student learning using the lab’s validated measures.
• Lead and co-author peer-reviewed papers (e.g., ACL, Learning@Scale, LAK, education research journals) and briefs for practitioners and developers, and present findings at academic conferences.
  

Implementation science, public goods, and team

• Document each partnership systematically, recording what was asked, what changed, what shipped, and what got in the way, and use these records to lead cross-case research on moving research into products.
  Prepare documentation and usage guides so other developers can adopt the lab’s released measures, evaluators, and toolkits, and contribute to dissemination.
• Formally supervise and train graduate and undergraduate research assistants on partner-facing projects, including hiring, performance management, and instruction on techniques.
• Complete project-related administrative and budgetary responsibilities of limited scope, such as tracking partner deliverables and coordinating data-use agreements with the project manager.
• Other duties may also be assigned.
  

To be successful in this position, you will bring

Minimum education and experience (required)
Graduate degree in an applicable social science related field and five years of applicable experience, or combination of education and relevant experience in an applicable social science. Relevant fields include education, learning sciences, education data science, economics, statistics, and computational social science.

Minimum knowledge, skills, and abilities (required)

• Expert level knowledge and skills in field of science related to our lab’s work.
• General computer skills and ability to quickly learn and master computer programs.
• Strong analytical skills and excellent judgment.
• Ability to work under deadlines with general guidance.
• Excellent organizational skills and demonstrated ability to complete detailed work accurately.
• Demonstrated oral and written communication skills.
• Ability to work with human study participants.
• Supervisory skills.
  

Also required for this role

• At least two years of your applicable experience at a technology company, ideally in education technology.
• Strong Python skills and experience analyzing large, messy, real-world data, such as product logs, text, or interaction data.
• Hands-on experience with large language models or NLP pipelines, including prompting, evaluation, and working through APIs.
• Experience designing and analyzing experiments or quasi-experiments.
• A record of research writing, such as papers, technical reports, or major contributions to either.
• Experience working with product teams or external partners to put research into use, including scoping shared work and following through.

Preferred

• K–12 teaching experience, especially in mathematics, or familiarity with high-quality instructional materials such as Illustrative Mathematics.
• A PhD in a relevant field.
• NLP or machine learning research experience.
• Familiarity with implementation science, improvement science, or research–practice partnerships, and with research data governance (data-use agreements, IRB).
• Experience working with multilingual learners, or proficiency in Spanish.

If you meet the required qualifications but not every preferred one, we encourage you to apply. People reach this work by many routes, for example from the classroom into edtech or from research into product, and we value that range.

Physical requirements

Frequently perform desk-based computer tasks, grasp lightly/fine manipulation, lift/carry/push/pull objects that weigh up to 10 pounds.

Occasionally stand/walk, sit, use a telephone, writing by hand, and sort/file paperwork or parts.

Rarely twist/bend/stoop/squat, kneel/crawl, rarely reach/work above shoulders, operate foot and/or hand controls.

Working conditions

May be exposed to blood borne pathogens.

May be required to work non-standard, extended or weekend hours in support of research work.

Work standards

Interpersonal Skills: Demonstrates the ability to work well with Stanford colleagues and clients and with external organizations.

Promote Culture of Safety: Demonstrates commitment to personal responsibility and value for safety; communicates safety concerns; uses and promotes safe behaviors based on training and lessons learned.

Subject to and expected to comply with all applicable University policies and procedures, including but not limited to the personnel policies and other policies found in the University’s Administrative Guide, http://adminguide.stanford.edu/.

How to apply

Please submit:

• A CV.
• A cover letter (up to 2 pages) describing a time you translated research into a product or practice, or a product question into research, and what you learned from it.
• One writing sample, such as a paper, technical report, or substantial blog post.

Applications will be reviewed on a rolling basis beginning November 16. Finalists will complete a short exercise drawn from the role’s day-to-day work. Stanford cannot provide visa sponsorship for this role. If you need an accommodation at any point in the process, please let us know.

Core Duties:

• Assist principal investigators with designing experiments constituting a phase of a research project for which precedents are few; conduct experiments that may involve coordinating a complex experimental protocol.

• Independently identify/modify standard procedures based on judgment concerning the general goals of a project; select approaches in developing, testing, and evaluating new methods.

• Lead or participate in multidisciplinary teams (in academia, across different faculties or schools, and in industry, across different functions of the business).

• Co-author all or sections of a report for publication or professional presentation with the work being reviewed by the principal investigator or faculty.

• Present ongoing work and findings to colleagues at academic conferences.

• Collaborate with the principal investigator to design a research approach of a project and/or integrate results of the entire project.

• Complete project-related administrative and budgetary responsibilities of a limited scope as needed.

• Formally supervise and train new staff or students, including hiring, performance management, and related duties, in addition to instruction on techniques and consultation on project work.

Minimum Education and Experience

Graduate degree in an applicable social science related field and five years of applicable experience, or combination of education and relevant –experience in an applicable social science.

Knowledge, Skills and Abilities:

• Expert level knowledge and skills in field of science related to research project.

• General computer skills and ability to quickly learn and master computer programs.

• Strong analytical skills and excellent judgment.

• Ability to work under deadlines with general guidance.

• Excellent organizational skills and demonstrated ability to complete detailed work accurately.

• Demonstrated oral and written communication skills.

• Ability to work with human study participants.

• Supervisory skills.