Clinical Research Fellowship in Artificial Intelligence & Machine Learning in Congenital Cardiac Care

Job Posting Title:

Clinical Research Fellowship in Artificial Intelligence & Machine Learning in Congenital Cardiac Care

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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:

40

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FLSA Status:

Exempt

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Earliest Start Date:

Immediately

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Position Duration:

Expected to Continue Until Jun 30, 2026

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Location:

UT MAIN CAMPUS

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Job Details:

General Notes

Co-sponsored by the Texas Center for Pediatric and Congenital Heart Disease (Dell Medical School at UT-Austin and Dell Children’s Medical Center) and AI Institute for Foundations of Machine Learning (IFML) at UT-Austin

Purpose

To facilitate the integration of artificial intelligence (AI) and machine learning (ML) by clinicians and researchers to advance the care of patients and the field of congenital heart disease (CHD).

Length: 2 years

Responsibilities

• Support the design and execution of research studies that apply AI/ML techniques to answer foundational problems in congenital cardiac care under the mentorship of clinician faculty from the Heart Center and computer science researchers at the Machine Learning Laboratory

• Participate in clinical, quality, and research conferences at the Heart Center

• Participate in a smaller clinical research projects with Heart Center faculty (to allow fellows to gain a broader understanding of clinical research and have significant academic productivity to allow them to be competitive for residency/fellowship)

• Option: Complete the Master’s of Artificial Intelligence Program at UT Austin (https://cdso.utexas.edu/msai)

• Potential for limited clinical work to maintain clinical skills (contingent upon eligibility and hospital system clearance.)

Examples of types of projects:

• Development of ML algorithms to predict clinical outcomes

• Diagnosis and screening of diseases or complications using high-fidelity data

• Use of large-language models to analyze qualitative data

• Analysis and identification of patterns from complex clinical data

• Creation of expected clinical trajectories based on large clinical datasets

Required Qualifications

MD, MD/PhD degree or equivalent. Passion and drive to advance the care of children and adults with congenital heart disease through technology and research. Working knowledge or experience with computer science, modeling, complex statistical analysisAbility to make a 2-year commitment to the program

Relevant education and experience may be substituted as appropriate.

Preferred Qualifications

2 years of clinical experience as part of a residency program. Undergraduate or graduate degree in computer sciences, mathematics, statistics, electrical engineering, computer engineering, artificial intelligence, or related sciences. Research experience in the medical field, ideally in fields related to computer science and complex statistical analysis. Strong interest in congenital heart disease and cardiovascular health.

Salary Range

$75,000 + depending on qualifications

Required Materials

• Resume/CV

• 3 work references with their contact information; at least one reference should be from a supervisor

• 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:

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