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Job Description

As a UW employee, you have a unique opportunity to change lives on our campuses, in our state and around the world. UW employees offer their boundless energy, creative problem-solving skills, and dedication to build stronger minds and a healthier world.

UW faculty and staff also enjoy outstanding benefits, professional growth opportunities and unique resources in an environment noted for diversity, intellectual excitement, artistic pursuits, and natural beauty.

The AmplifyLearn.AI Center at the University of Washington is at the forefront of integrating artificial intelligence and machine learning (AI/ML) into education. Our mission is to develop innovative AI/ML methods, study AI adoptions in educational settings, and create technology solutions that enhance K-12 learning experiences. The Center focuses on four key areas: Research, Technology Development, Training, and Public Engagement. The Center's work is generously funded by the Institute of Education Sciences (IES), the National Science Foundation (NSF), and among others, enabling us to pursue cutting-edge research and development in AI for education.

We are seeking a Senior Research Associate (AI for Education) to contribute to the Center’s work at the intersection of artificial intelligence and K–12 education. Reporting to the Assistant Director, Dr. Lief Esbenshade, this role will assist in the center's two strands of work: Research and Technology Development. Among other responsibilities, the Senior Research Associate will focus on implementing and evaluating large language model (LLM) methods in educational contexts, contributing to studies of AI adoption and instructional design, and co-authoring publications. The Associate will also collaborate with Colleague AI, an EdTech startup partner, to prototype and assess technology solutions for teachers and students. Candidates should have strong programming skills (python preferred), experience with LLMs, and familiarity with education or learning sciences research.

DUTIES AND RESPONSIBILITIES

Research Execution 50%

+ Implement research methodologies in AI/ML for education, including running experiments, analyzing data, and developing reproducible workflows.

+ Contribute to empirical studies of AI adoption and instructional design in K–12 classrooms, including data collection, cleaning, and analysis.

+ Adapt and apply evaluation frameworks from other AI domains to assess LLM outputs in education; co-author technical reports and publications based on findings.

Technology Development 20%

+ Implement and adapt large language model (LLM) methods for K–12 educational contexts, with a focus on evaluation and classroom relevance.

+ Prototype and refine AI-powered tools in collaboration with the Colleague AI team, ensuring usability and alignment with educational needs.

+ Develop and maintain pipelines for model evaluation, data processing, and experimental deployment to support ongoing research projects.

Collaboration and Support 15%

+ Work closely with faculty and graduate students to advance joint projects in AI and education.

+ Provide technical guidance to research assistants and graduate student contributors on coding, data analysis, and use of AI/ML tools.

+ Coordinate with the assistant director to ensure project deliverables are completed on schedule and aligned with broader research goals.

Dissemination and Engagement 15%

+ Contribute to conference papers, journal articles, and technical reports on AI in education, with a focus on LLM evaluation and applied research findings.

+ Support workshops, demos, and presentations for educators and partners by preparing research materials, prototypes, and results.

+ Assist in communicating research outcomes to academic, practitioner, and public audiences in accessible formats.

Minimum Requirements:

+ Bachelor's degree in Education, Computer Science, Data Sciences, or a related field and 4+ years conducting applied research in K–12 education, with evidence of direct work on classroom practice, instructional design, or technology adoption.

Additional Requirements:

+ Strong programming skills including proficiency in Python, experience with version control (Git), and working with databases

+ Experience with AI/ML frameworks (e.g., PyTorch, Hugging Face, OpenAI/Anthropic APIs)

+ Demonstrated ability to contribute to collaborative research projects, including data analysis, prototyping, and documentation.

+ Excellent communication skills, with the ability to translate technical results for educators and non-technical stakeholders

+ Ability to work independently while contributing effectively within a multidisciplinary team.

Desired Qualifications:

+ Master's degree in Education, Computer Science, Data Sciences or a related field and 3+ years of experience conducting applied research in K–12 education, with evidence of direct work on classroom practice, instructional design, or technology adoption.

+ Publication record in academic journals or conferences relevant to AI, education, or human-computer interaction.

+ Experience with U.S. K–12 education systems (e.g., as a researcher, teacher, or administrator).

+ Familiarity with educational policies and practices in the United States.

+ Experience developing or evaluating educational technologies in classroom or district settings.

+ Experience with cloud computing environments including AWS, Azure, or Google Cloud

The initial application should include:

(1) A statement of interest. This statement should introduce the applicant and explain their interest in the position. It should highlight the applicant's relevant skills, qualifications, and experience, as well as explain how they can lead the research and product development initiatives of AI/ML in education.

(2) Curriculum vitae. This document provides an overview of the applicant’s education work experience, publications, research projects, and other relevant qualifications.

(3) Examples of prior work that demonstrates qualifications of the job description, which includes scholarly publications, Github Repos, or website built.

Compensation, Benefits and Position Details

Pay Range Minimum:

$89,544.00 annual

Pay Range Maximum:

$117,996.00 annual

Other Compensation:

-

Benefits:

For information about benefits for this position, visit https://www.washington.edu/jobs/benefits-for-uw-staff/

Shift:

First Shift (United States of America)

Temporary or Regular?

This is a regular position

FTE (Full-Time Equivalent):

100.00%

Union/Bargaining Unit:

UAW Research

About the UW

Working at the University of Washington provides a unique opportunity to change lives – on our campuses, in our state and around the world.

UW employees bring their boundless energy, creative problem-solving skills and dedication to building stronger minds and a healthier world. In return, they enjoy outstanding benefits, opportunities for professional growth and the chance to work in an environment known for its diversity, intellectual excitement, artistic pursuits and natural beauty.

Our Commitment

The University of Washington is proud to be an affirmative action and equal opportunity employer (https://hr.uw.edu/eoaa/) . All qualified applicants will receive consideration for employment without regard to race, color, religion, sex, sexual orientation, gender identity, gender expression, national origin, age, protected veteran or disabled status, or genetic information.

To request disability accommodation in the application process, contact the Disability Services Office at 206-543-6450 or [email protected] .

Applicants considered for this position will be required to disclose if they are the subject of any substantiated findings or current investigations related to sexual misconduct at their current employment and past employment. Disclosure is required under Washington state law (https://app.leg.wa.gov/RCW/default.aspx?cite=28B.112.080) .

University of Washington is an affirmative action and equal opportunity employer. All qualified applicants will receive consideration for employment without regard to, among other things, race, religion, color, national origin, sexual orientation, gender identity, sex, age, protected veteran or disabled status, or genetic information.