Postdoctoral fellow in AI for medical image analysis

Sunday 27th June 2021

Organization: Johns Hopkins University

Location: Baltimore, MD, USA


Email Address:

 Closing Date: September 30, 2021


Medical Image Computing and Analysis (MICA) Laboratory ( in the Division of Medical Physics, Department of Radiation Oncology and Molecular Radiation Sciences at John Hopkins University School of Medicine has a postdoctoral research fellow position opening for a highly qualified personnel to work on research in medical image processing and analysis, artificial intelligence (AI), and image-guided radiation therapy.

Multidisciplinary teams of radiation oncologists, radiologists, imaging scientists, physicists, and company collaborators are working on real-time multi-modal image-guided prostate cancer radiotherapy and MR-guided gynecologic cancer radiotherapy where the fellow will work on AI-based normal tissue segmentation, multi-parametric MRI-based tumor classification, multi-modal image registration, and signal and image processing for real-time image guidance and outcome prediction.

An ideal candidate should have Ph.D. in biomedical or electrical engineering, computer science, or medical physics with a strong background and interest in medical image processing/analysis and machine learning. Programming experience in python, Matlab, C++, ITK/VTK, CUDA, tensorflow, pytorch is a plus.

This is an exciting research opportunity to learn and work on latest and cutting edge techniques in medical image processing, machine learning, MRI, and image-guided interventions in collaboration with multi-disciplinary team. Interested applicants should send their CV and names of three professional references to:

Junghoon Lee, Ph.D. Associate Professor Division of Medical Physics Department of Radiation Oncology and Molecular Radiation Sciences Johns Hopkins University School of Medicine Email:

The Johns Hopkins University is an EEO/AA Employer. The Department of Radiation Oncology and Molecular Radiation Sciences is committed to building a diverse educational environment, and women and minorities are strongly encouraged to apply.