Postdoc: AI for Medical Imaging & Precision Oncology

Atrium Health; Winston-Salem (NC); On-site; USD 52,000 - 65,000; Full time

Job summary

The Laboratory at Wake Forest University School of Medicine is seeking two Postdoctoral Researchers to join our NIH-funded interdisciplinary research program in artificial intelligence, medical imaging, computational pathology, and precision oncology.

Postdoctoral Fellows will lead development of ML/DL methods for medical imaging, design and evaluate AI algorithms on radiology, pathology, genomic, and clinical data, publish in top journals, present findings at meetings, and mentor students and

Qualifications

• PhD in a quantitative field as listed.
• Strong background in ML/DL/CV or multimodal AI.
• Ability to conduct independent research while collaborating.

Responsibilities

• Developing novel machine learning and deep learning methodologies for medical imaging, computational pathology, and multimodal biomedical data analysis.
• Designing, implementing, and evaluating AI algorithms using large-scale radiology, pathology, genomic, transcriptomic, and clinical datasets.
• Publishing research in leading biomedical and artificial intelligence journals and conferences.
• Presenting research findings at national and international scientific meetings.
• Mentoring graduate students, medical students, and research staff.
• Establishing collaborations with investigators across multiple disciplines and institutions.

Skills

Machine learning

Deep learning

Computer vision

Multimodal AI

Education

PhD in Artificial Intelligence, Biomedical Engineering, Computer Science, Electrical or Computer Engineering, Bioinformatics, Data Science, Statistics, or a closely related quantitative discipline

Job description

The Laboratory at Wake Forest University School of Medicine is seeking two Postdoctoral Researchers to join our NIH-funded interdisciplinary research program in artificial intelligence, medical imaging, computational pathology, and precision oncology.

Postdoctoral Fellows will lead development of ML/DL methods for medical imaging, design and evaluate AI algorithms on radiology, pathology, genomic, and clinical data, publish in top journals, present findings at meetings, and mentor students and