Our research is centered on the development and application of novel, trustworthy machine learning (ML) and artificial intelligence (AI) solutions to address significant healthcare challenges and emerging biomedical problems. You will work with large-scale electronic health data including electronic health records, clinical notes, signals, or multi-omics data across various healthcare domains.
Current University of Minnesota students who are interested in our research are encouraged to reach out. Additionally, we welcome visiting students from other universities who are keen to collaborate on our projects onsite or remotely.
🔬 Research Focus
Our lab specializes in Health Data Science and Medical Informatics, with research areas including:
- Mining and analyzing large-scale healthcare data
- Trustworthy machine learning (ML/AI): interpretability, fairness, and reproducibility
- Integration of multimodal data, such as structured Electronic Health Records (EHRs), clinical narratives, and Natural Language Processing (NLP)
- Clinical deployment of AI models in high-stakes settings including emergency care, critical care, and neonatology
- Topics include disease prediction, prognosis modeling, clinical decision support, and personalized treatment recommendations
We aim not only to develop new methods, but also to produce clinically impactful research. Our work is guided by a clear goal: publication in high-impact medical journals such as JAMA Network, The Lancet Digital Health, and npj Digital Medicine, with the intention of translating data science into real-world healthcare solutions.
👨🏫 About the PI and the Lab
The lab is led by an Assistant Professor at the University of Minnesota Medical School, with expertise in medical AI, EHR modeling, and algorithmic fairness. The PI has international experience from Singapore and Stanford, and has published in top-tier journals and developed widely adopted open-source tools. 🔗 PI’s homepage: https://fengx13.github.io/
📌 Open Positions & Requirements
Postdoctoral Fellows / Research Assistants (RA)
- Strong programming skills in Python, R, or SQL
- Strong research experience with:
- Deep learning
- Foundation models
- Clinical NLP & language models
- Large-scale EHR or biomedical data
- 💡 *Exceptional RAs may be considered for PhD admission, depending on qualifications and availability *
Internships/Collaboration
- For motivated individuals who may lack extensive experience but are eager to learn
- Interns may start with collaborative projects
⭐ Why Join Us
Exclusive Data Access:
Collaborate with a major academic medical center with access to millions of patient records, including structured and unstructured data across a wide range of diseases.Impactful Publications:
Founded less than a year ago, the lab already has several student first-author manuscripts in progress. We emphasize high-quality, clinically relevant publications at high-impact journals over CS conference papers.Strong Infrastructure:
Well-established data pipelines, robust computing resources, and advanced tooling to support efficient, scalable research.
🏫 University & Location
The University of Minnesota is a top-ranked public research university in the U.S., with over $1.2 billion in annual research funding. It is especially well known for its strengths in engineering and medical sciences, consistently ranking in the top 20 nationwide.
Located in Minneapolis–St. Paul, the Twin Cities offer a high quality of life, vibrant academic and tech communities, and excellent job opportunities — all at a relatively low cost of living.
📥 How to Apply
We welcome students and researchers interested in medical AI, health data science, and informatics to join our collaborative team! Important Information
- If you are interested in any position (Postdoc, PhD, Research Assistant, Internship, etc) with us, please fill out this form.
- Any questions can be sent to Dr. Feng Xie (xie00469@umn.edu).
- Please note that the review process may take time, and only shortlisted candidates will be contacted for further steps.