Su-In Lee
Top university
10 months ago
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Postdoctoral Positions in Explainable AI for Biomedical Research (Alzheimer’s, Aging, Cancer, Medical AI) University of Washington in United States
Degree Level
Postdoc
Field of study
Computer Science
Funding
Positions are NIH-funded and may include additional support from institutional and consortium grants. Funding covers salary and research expenses; specific stipend amounts are not listed but are competitive for postdoctoral roles at the University of Washington.
Deadline
Expired
Country
United States
University
University of Washington
Suggested positions
Keywords
About this position
The AIMS lab at the University of Washington, led by Boeing Endowed Professor Su-In Lee, is recruiting multiple postdoctoral researchers to advance the frontiers of explainable AI (XAI) in biomedical research. The lab is internationally recognized for pioneering the SHAP framework and other foundational algorithms in XAI and computational biomedicine, with transformative discoveries acknowledged by awards such as the 2024 ISCB Innovator Award.
Research in the lab spans core AI/ML innovations and their application to biomedical domains, including Alzheimer’s disease, aging biology, cancer precision medicine, and trustworthy medical AI. Projects integrate AI with diverse biomedical data types: single-cell and multi-omics, biomedical images (cell painting, pathology, radiology, ophthalmology, dermatology), health records, DNA/protein sequences, and biomedical text. The lab’s work opens new frontiers in understanding health, disease, and therapeutics.
Key research directions include:
- Developing interpretable, controllable, and multimodal AI/ML models.
- Applying XAI for agent and autonomous reasoning in science.
- Ensuring transparency, safety, and robust explanations for biomedical AI systems.
Biomedical research directions focus on:
- Alzheimer’s therapeutic target discovery using multimodal data and XAI (NIH-funded).
- Aging biology and rejuvenation research integrating multi-omic and population data (NIH-funded).
- Cancer precision medicine through interpretable biomarkers and multimodal datasets (ARPA-H consortium).
- Interpretable multimodal embeddings for genes, proteins, cells, and images.
- XAI for medical imaging, including clinical audit and interpretation (NIH-funded).
Postdocs will collaborate with biologists and clinicians, contributing to translational breakthroughs in biomedicine. Candidates should have a PhD in computer science, biomedical engineering, computational biology, or related fields, with strong expertise in AI/ML and biomedical data. Funding is provided through NIH and institutional grants, covering salary and research expenses. Applications are open for immediate start; see the lab’s LinkedIn and academic page for details.
Funding details
Positions are NIH-funded and may include additional support from institutional and consortium grants. Funding covers salary and research expenses; specific stipend amounts are not listed but are competitive for postdoctoral roles at the University of Washington.
What's required
Applicants should hold a PhD in computer science, biomedical engineering, computational biology, or a related field. Strong expertise in AI/ML, especially explainable AI, and experience with biomedical data (omics, imaging, health records, etc.) are highly preferred. Candidates should have a track record of research excellence, strong programming and analytical skills, and the ability to work collaboratively in interdisciplinary teams. Immediate availability is preferred.
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Prepare your application
Review drafts and confirm requirements with the university.
Professors
Boeing Endowed Professor
United States
Research Interests
Biostatistics
Medical Imaging
Explainability
Omics
Machine Learning In Healthcare
Make your next move.
Prepare your application
Review drafts and confirm requirements with the university.