Graduate Assistant, Pediatrics

Job Posting Title:

Graduate Assistant, Pediatrics

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Hiring Department:

Department of Pediatrics

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Position Open To:

All Applicants

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Weekly Scheduled Hours:

19

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FLSA Status:

Non-Exempt

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Earliest Start Date:

Dec 15, 2025

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Position Duration:

Expected to Continue Until Dec 14, 2026

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Location:

UT MAIN CAMPUS

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Job Details:

Purpose

This position will support two current national projects using the graduate research assistant’s knowledge and skill in data governance, data extraction, statistical data analysis, and data visualization. The GRA’s support will not only ensure meeting grant/award deliverables but will also maximize the project’s data platform benefit to emergency department participants across the U.S. This position is slated through 12/31/2026 but has the possibility of ending early if all project/tasks are completed early.

Responsibilities

• Data extraction and transformation: Querying and extracting largescale clinical datasets (approximately 10 million pediatric encounters) using SQL and transforming data into the OMOP Common Data Model (CDM) for analysis.
• Feature engineering and ETL support: Performing feature engineering, data cleaning, and ETL pipeline development to prepare structured, analysis-ready datasets
• Predictive modeling and statistical analysis: Applying statistical and machine learning techniques (e.g., Python, scikit-learn, pandas, PyTorch) to forecast outcomes and identify key trends in pediatric emergency care
• Model validation and documentation: Conducting model evaluation and performance tracking, documenting reproducible workflows using tools such as MLflow or equivalent
• Data visualization and reporting: Creating interactive dashboards and visualizations to communicate analytical insights and quality-improvement metrics to physicians and program stakeholders
• Collaboration and dissemination: Working closely with physicians, data scientists, and quality-improvement experts to interpret findings, prepare reports, and contribute to manuscripts and publications
• Compliance and data governance: Ensuring secure handling of clinical data, following institutional data governance and HIPAA-compliant de-identification procedures

Required Qualifications

• Bachelor’s degree in Computer Science, Information Science, Data Science or related technical field
• Current enrollment in a UT Austin graduate program within one of the above areas
• Ability to work independently and in collaboration with interdisciplinary teams

Education and demonstrated experience with the following:

• Programming experience (e.g., Python, JavaScript, or similar).
• Python (e.g., data structures, API integration, automation) and modern web frameworks (e.g., React, Next.js) for interface development.
• Large language models (LLMs) and/or natural language processing (NLP) concepts.
• Retrieval-augmented generation (RAG) or integration of large language models (LLMs) into applications
• Machine learning
• Azure/AWS
• SDKs and APIs
• Data governance and compliance
• Data cleaning and preparation for analysis
• Streamlining data collection for audit readiness
• Predictive modeling and statistical analysis
• Building dashboards and data visualizations

Relevant education and experience may be substituted as appropriate.

Preferred Qualifications

• Experience building or automating evaluation pipelines (e.g., factuality checks, citation fidelity, benchmarking).
• Familiarity with biomedical or healthcare data sources (e.g., PubMed, EHRs) or other domain-specific corpora.

Prior research experience in health informatics or related field.

Salary Range
$35.00

Working Conditions

• Repetitive use of a keyboard at a workstation

Required Materials

• Resume/CV

• 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.