Fully Funded PhD Position in AI for Healthcare and Diabetes Pharmacotherapy at University of Utah University of Utah in United States

The Department of Biomedical Informatics at the University of Utah is recruiting a fully funded PhD student for Fall 2026 under the supervision of Assistant Professor Polina Kukhareva. The research group focuses on AI for healthcare, with a special emphasis on diabetes pharmacotherapy, causal inference, and clinical decision support. Students will have the opportunity to work with some of the largest electronic health record (EHR) datasets in the world, developing advanced machine learning models such as LSTMs, GRUs, Transformers, and causal ML to predict treatment outcomes and improve clinical care.

Research topics include learning treatment trajectories from medication histories, predicting changes in HbA1c, weight, and hypoglycemia, estimating individualized treatment effects, and advancing fairness, transparency, and generalizability in clinical AI. The lab values honesty, clear communication, scientific integrity, and continuous learning through supportive mentorship.

Applicants should have a master's degree in computer science, data science, or a related field, with strong skills in Python and PyTorch/TensorFlow. Interest in healthcare AI and a commitment to collaboration and growth are essential. Preferred qualifications include experience with deep learning architectures, causal inference, real-world evidence, and large datasets. University requirements include a bachelor's degree, minimum GPA of 3.3, CV, personal statement, three letters of recommendation, transcripts, and prerequisite courses in programming, statistics, and basic biology.

The position offers multi-year funding, access to national-scale EHR data, high-performance computing resources, interdisciplinary mentorship, and professional development support. The application deadline is December 31, 2025. For full details and to apply, visit the university admissions page linked in the post.