Post Doc Research Fellow-AI​/ML Medical Image Analysis

Hourly Pay Range

$0.00 - $0.00 - The hourly pay rate offered is determined by a candidate's expertise and years of experience, among other factors.

$0.00 - $0.00 - The hourly pay rate offered is determined by a candidate's expertise and years of experience, among other factors.

• Position:
  Postdoctoral Research Fellow – AI/ML Medical Image Analysis
• Location:
  
  Evanston, IL
• Full Time/Part Time:
  Full Time
• Hours:
  
  Monday–Friday, with flexible work schedules

Endeavor Health is seeking a talented Postdoctoral Research Fellow specializing in AI/ML with experience in medical image analysis to join our research enterprise at Endeavor Health Evanston Hospital, an educational affiliate of the University of Chicago (Evanston, IL). This position will establish a cross-cutting AI/ML imaging core serving four high-impact research groups: gynecology, urogynecology, obstetrics/pathology, and radiology.

Endeavor Health has built nationally recognized strength in gynecology, urogynecology, obstetrics, and radiology research, generating rich datasets including uterine cine MRI, pelvic floor ultrasound, digital placental pathology, kidney functional MRI, and multimodal pain biomarkers. This position offers the opportunity to work with highly successful translational teams (see ) to provide dedicated AI/ML expertise in image analysis to automate MRI segmentation, perform large-scale histological analyses, and develop predictive imaging models.

The Postdoctoral Research Fellow will be embedded in four collaborative research teams and mentored toward independence as a future principal investigator, with structured support for K- and R-level extramural grant applications. The fellow will work closely with senior investigators. The research environment includes multiple active federally funded projects and a strong track record of high-impact publications and trainee career advancement.

• Design and deploy scalable AI pipelines for automated uterine, placental, pelvic and kidney MRI segmentation.
• Develop multimodal predictive models integrating imaging, molecular, and clinical data to predict chronic pain risk and other clinical outcomes.
• Implement explainable AI (XAI) approaches to ensure transparency and rigor across pipelines.
• Disseminate AI pipelines as shared institutional tools to broaden adoption across research groups.
• Collaborate actively with gynecology, obstetrics/pathology, and radiology teams.
• Regularly review scientific literature and evaluate emerging AI/ML techniques and procedures.
• Co-author scientific papers for presentation and publication.
• Contribute to grant writing, targeting R01/U01 applications; prepare for independent K- and R-level award applications.
• Present work at institutional seminars and scientific meetings to promote AI/ML adoption.
• Consult with research personnel in research design, AI/ML methodology, and scientific inference.
• As requested, mentor or teach others in AI/ML methods requiring advanced technical knowledge.
• Demonstrates knowledge of Endeavor customer service standards and North Shore University Endeavor policies and procedures applicable to the role.
• Participates in ongoing professional development through workshops, in-service programs, and professional meetings.
• Performs related duties as required or assigned.

• Education:
  
  PhD in Biomedical Engineering, Computer Science, Electrical Engineering, Biomedical Informatics, or closely related field required.
• Experience:
  
  Demonstrated expertise in deep learning and computer vision for medical image analysis (MRI, ultrasound, histopathology, or similar modalities). Proficiency in Python and relevant AI/ML frameworks (e.g., PyTorch, Tensor Flow, scikit-learn). A publication record and sample code demonstrating AI/ML image analysis capabilities.
  
  Experience with medical imaging data formats and preprocessing pipelines (e.g., DICOM, NIfTI, ITK/Simple
  
  ITK). Familiarity with explainable AI methods and best practices for model transparency. Experience with or interest in multimodal data integration (imaging, molecular, clinical). Able to work collaboratively across multiple research groups and manage…