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Su-In Lee

Top university

10 months ago

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 flag

Country

United States

University

University of Washington

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Keywords

Computer Science
Biomedical Engineering
Biology
Computational Biology
Aging
Alzheimer's Disease
Neuropsychology
Medical Science
Omics
Explainability
ML

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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Professors

Boeing Endowed Professor

University Name
Country flag

United States

Research Interests

Biostatistics

Medical Imaging

Explainability

Omics

Machine Learning In Healthcare