Graduate Research Assistant (LLM Interaction and Statistical Analysis)

Job Posting Title:

Graduate Research Assistant (LLM Interaction and Statistical Analysis)

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Hiring Department:

IC2 Institute

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Position Open To:

All Applicants

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Weekly Scheduled Hours:

20

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FLSA Status:

Exempt from FLSA

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Earliest Start Date:

Immediately

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Position Duration:

Expected to Continue Until Aug 31, 2026

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Location:

UT MAIN CAMPUS

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Job Details:

General Notes

Under the direction of the Learning Lab leadership team, the employee will contribute to the design and implementation of research involving medical learners’ interactions with generative AI tools. The appointment is on a semester-by-semester basis.

Position is eligible for Tuition Reduction Benefit (TRB) and is determined by the number of hours employed per week during the semester

Purpose

The GRA will work extensively with LLM-related data, including chat transcripts, structured interaction logs, usage metadata, and quantitative evaluation measures (e.g., rubrics and surveys). The primary emphasis of this role is statistical and computational analysis of clinician–LLM interactions and their relationship to clinical reasoning outcomes. This role provides hands-on experience at the intersection of data science, clinical reasoning research, and human–AI interaction, contributing to empirical analyses of how LLMs are used in real clinical reasoning tasks.

Responsibilities

• Analyze LLM chat logs and interaction metadata (e.g., turn taking, prompt types, revision behavior)

• Conduct statistical analyses combining LLM data with structured measures (rubrics, surveys)

• Support mixed methods synthesis in collaboration with qualitative researchers

• Prepare internal analytic memos documenting methods, findings, and implications

• Contribute figures, tables, and methods text for academic papers and white papers

Required Qualifications

• Bachelor’s degree in data science, cognitive science, psychology, informatics, communication, social science, or related field.

• Experience working with quantitative data and computational analysis.

• Experience conducting statistical or computational analysis

• Experience working with text-based or interaction data (e.g., chat logs)

• Familiarity with R or Python preferred

• Strong organizational skills and attention to detail.

• Ability to manage secure data and respect confidentiality protocols.

• Ability to work independently and collaboratively. 

Relevant education and experience may be substituted as appropriate.

Preferred Qualifications

• Minimum of Master’s level coursework in data science, informatics, psychology, or related fields.

• Experience with Python or R for text analysis, NLP, or data wrangling.

• Experience with human–AI interaction or clinical/medical education settings.

• Experience contributing to IRB submissions. 

Salary Range

$33,108

Working Conditions

• Typical office environment

• Remote work environment with occasional in-person meetings

• GRA’s will use their own computers

Work Shift

• Fall/Spring Semesters: up to 20 hours per week; Summer months up to 40 hours per week.

• M-F, 8 am - 5 pm

• Nominally, in-person at the IC2 Institute, however, some occasional remote work is currently permitted

• Flexible hours to be arranged with supervisor

Required Materials

• Resume/CV

• 3 work references with their contact information; at least one reference should be from a supervisor and at least one reference should be from a faculty member familiar with the student’s related skills and experience.

• Letter of interest

Important for applicants who are NOT current university employees or contingent workers: You will be prompted to submit your resume the first time you apply, then you will be provided an option to upload a new Resume for subsequent applications. Any additional Required Materials (letter of interest, references, etc.) will be uploaded in the Application Questions section; you will be able to multi-select additional files. Before submitting your online job application, ensure that ALL Required Materials have been uploaded.  Once your job application has been submitted, you cannot make changes.

Important for Current university employees and contingent workers: As a current university employee or contingent worker, you MUST apply within Workday by searching for Find UT Jobs. If you are a current University employee, log-in to Workday, navigate to your Worker Profile, click the Career link in the left hand navigation menu and then update the sections in your Professional Profile before you apply. This information will be pulled in to your application. The application is one page and you will be prompted to upload your resume. In addition, you must respond to the application questions presented to upload any additional Required Materials (letter of interest, references, etc.) that were noted above.

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Employment Eligibility:

Please confirm your eligibility for this position here: http://www.utexas.edu/hr/student/student_acad_employment.html

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Retirement Plan Eligibility:

Students in this position may choose to enroll in the UTSaver voluntary retirement programs.

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Background Checks:

A criminal history background check will be required for finalist(s) under consideration for this position.

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Equal Opportunity Employer:

The University of Texas at Austin, as an equal opportunity/affirmative action employer, complies with all applicable federal and state laws regarding nondiscrimination and affirmative action. The University is committed to a policy of equal opportunity for all persons and does not discriminate on the basis of race, color, national origin, age, marital status, sex, sexual orientation, gender identity, gender expression, disability, religion, or veteran status in employment, educational programs and activities, and admissions.

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Pay Transparency:

The University of Texas at Austin will not discharge or in any other manner discriminate against employees or applicants because they have inquired about, discussed, or disclosed their own pay or the pay of another employee or applicant. However, employees who have access to the compensation information of other employees or applicants as a part of their essential job functions cannot disclose the pay of other employees or applicants to individuals who do not otherwise have access to compensation information, unless the disclosure is (a) in response to a formal complaint or charge, (b) in furtherance of an investigation, proceeding, hearing, or action, including an investigation conducted by the employer, or (c) consistent with the contractor’s legal duty to furnish information.

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Employment Eligibility Verification:

If hired, you will be required to complete the federal Employment Eligibility Verification I-9 form.  You will be required to present acceptable and original documents to prove your identity and authorization to work in the United States.  Documents need to be presented no later than the third day of employment.  Failure to do so will result in loss of employment at the university.

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E-Verify:

The University of Texas at Austin use E-Verify to check the work authorization of all new hires effective May 2015. The university’s company ID number for purposes of E-Verify is 854197. For more information about E-Verify, please see the following:

• E-Verify Poster (English and Spanish) [PDF]
• Right to Work Poster (English) [PDF]
• Right to Work Poster (Spanish) [PDF]

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Compliance:

Employees may be required to report violations of law under Title IX and the Jeanne Clery Disclosure of Campus Security Policy and Crime Statistics Act (Clery Act). If this position is identified a Campus Security Authority (Clery Act), you will be notified and provided resources for reporting. Responsible employees under Title IX are defined and outlined in HOP-3031.

The Clery Act requires all prospective employees be notified of the availability of the Annual Security and Fire Safety report. You may access the most recent report here or obtain a copy at University Compliance Services, 1616 Guadalupe Street, UTA 2.206, Austin, Texas 78701.