Job Summary

We are seeking a temporary Programmer Analyst to join a research team focused on advancing the use of artificial intelligence (AI) in digital health interventions. This position will support a project led by Dr. Nirali Shah that aims to refine and personalize an AI-supported health coaching chatbot, Sprout, developed for individuals with systemic sclerosis (scleroderma). The chatbot is integrated into the RENEW mobile health intervention, which promotes fatigue self-management through education, goal setting, and behavioral support.

The Programmer Analyst will assist in enhancing the chatbot?s performance by integrating clinical data (e.g., disease severity, duration, symptom profiles) and user preference data into an existing large language model (UM GPT-4o). The role involves implementing advanced machine learning techniques such as transfer learning and fine-tuning, evaluating model performance, and collaborating with clinical and research staff. 

Responsibilities*

• Preprocess, clean, and manage clinical and patient-reported datasets to prepare them for machine learning applications 
• Help decide the type of AI model best suited for our use case, test, and integrate it within the RENEW mobile app
• Refine and fine-tune the AI model using structured clinical data, self-reported symptoms, and participant preferences
• Evaluate AI model performance using established metrics (e.g., accuracy, relevance, hallucination/error rate) and conduct iterative testing 
• Document code, workflows, and model refinements for reproducibility, reporting, and future grant submissions

Required Qualifications*

• Bachelor's Degree and work on a project that involved advanced machine learning skills

Modes of Work

Positions that are eligible for hybrid or mobile/remote work mode are at the discretion of the hiring department. Work agreements are reviewed annually at a minimum and are subject to change at any time, and for any reason, throughout the course of employment. Learn more about the work modes.

Background Screening

Michigan Medicine conducts background screening and pre-employment drug testing on job candidates upon acceptance of a contingent job offer and may use a third party administrator to conduct background screenings.  Background screenings are performed in compliance with the Fair Credit Report Act. Pre-employment drug testing applies to all selected candidates, including new or additional faculty and staff appointments, as well as transfers from other U-M campuses.

Application Deadline

Job openings are posted for a minimum of seven calendar days.  The review and selection process may begin as early as the eighth day after posting. This opening may be removed from posting boards and filled anytime after the minimum posting period has ended.

U-M EEO Statement

The University of Michigan is an equal employment opportunity employer.