Postdoc: AI for Medical Imaging & Oncology

Advocate Health; Winston-Salem (NC); On-site; USD 42,000 - 63,000; Full time

Benefits offered by this job

Health benefits

Paid time off

Retirement plan

Educational assistance

Job summary

The Laboratory at Wake Forest University School of Medicine, in collaboration with Advocate Health, is seeking two Postdoctoral Researchers to advance NIH-funded work in artificial intelligence, medical imaging, computational pathology, and precision oncology. Candidates will explore multimodal data and publish in top journals.

Responsibilities include developing AI methods for radiology and pathology, presenting at conferences, mentoring students, and fostering cross-institution collaborations.

Qualifications

• PhD in Artificial Intelligence, Biomedical Engineering, Computer Science, Electrical or Computer Engineering, Bioinformatics, Data Science, Statistics, or a closely related quantitative discipline.
• Strong background in machine learning, deep learning, computer vision, or multimodal AI.
• Ability to conduct independent research while working effectively in a collaborative environment.

Responsibilities

• Develop novel machine learning and deep learning methods for medical imaging, computational pathology, and multimodal data.
• Design, implement, and evaluate AI algorithms on large-scale radiology, pathology, genomic, transcriptomic, and clinical datasets.
• Publish research in leading biomedical and AI journals and conferences.
• Present findings at national and international scientific meetings.
• Mentor graduate students, medical students, and research staff.
• Establish collaborations with investigators across disciplines and institutions.

Skills

Machine learning

Deep learning

Computer vision

Multimodal AI

Independent research

Collaboration

Education

PhD in AI/BI Eng/CS/EE or related

Job description

The Laboratory at Wake Forest University School of Medicine, in collaboration with Advocate Health, is seeking two Postdoctoral Researchers to advance NIH-funded work in artificial intelligence, medical imaging, computational pathology, and precision oncology. Candidates will explore multimodal data and publish in top journals.

Responsibilities include developing AI methods for radiology and pathology, presenting at conferences, mentoring students, and fostering cross-institution collaborations.