Postdoctoral Researcher
Thursday 2nd May 2024
Contact Email for the Job Postingjunghoon@jhu.edu
OrganizationJohns Hopkins University
LocationBaltimore, Maryland, United States
TitlePostdoctoral Researcher
URLhttps://mica.jhu.edu/
Closing dateAug 31, 2024
DescriptionMedical Image Computing and Analysis (MICA) Lab in the Division of Medical Physics, Department of Radiation Oncology and Molecular Radiation Sciences, and also affiliated with the Carnegie Center for Surgical Innovation at Johns Hopkins University has multiple postdoctoral research fellow positions opening for a highly qualified personnel to work on research in medical image processing and analysis using artificial intelligence (AI) technology.
Multidisciplinary team of biomedical engineers, computer scientists, physicists, and physicians are working on image-guided surgery and radiation therapy problems in which the fellow will work on AI-based organ segmentation, multi-modal image registration, real-time image guidance, treatment planning, and multi-modal image analysis for treatment response prediction/assessment. Areas of major interest include limited-angle cone-beam CT reconstruction for intra-treatment motion management in pelvis and thorax, multi-contrast MR (anatomic, DWI, DTI, fMRI) image analysis for brain, and robot-assisted image-guided cardiovascular and neurovascular interventions.
An ideal candidate should have a 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, multi-modality imaging, and image-guided interventions in collaboration with multi-disciplinary team.
Interested applicants should send their CV and names of three professional references to Dr. Junghoon Lee [junghoon(at)jhu.edu].
| Contact Email for the Job Positing | junghoon@jhu.edu |
|---|---|
| Organization | Johns Hopkins University |
| Location | Baltimore, Maryland, United States |
| Title | Postdoctoral Researcher |
| URL | https://mica.jhu.edu/ |
| Closing date | Aug 31, 2024 |
| Description | Medical Image Computing and Analysis (MICA) Lab in the Division of Medical Physics, Department of Radiation Oncology and Molecular Radiation Sciences, and also affiliated with the Carnegie Center for Surgical Innovation at Johns Hopkins University has multiple postdoctoral research fellow positions opening for a highly qualified personnel to work on research in medical image processing and analysis using artificial intelligence (AI) technology. Multidisciplinary team of biomedical engineers, computer scientists, physicists, and physicians are working on image-guided surgery and radiation therapy problems in which the fellow will work on AI-based organ segmentation, multi-modal image registration, real-time image guidance, treatment planning, and multi-modal image analysis for treatment response prediction/assessment. Areas of major interest include limited-angle cone-beam CT reconstruction for intra-treatment motion management in pelvis and thorax, multi-contrast MR (anatomic, DWI, DTI, fMRI) image analysis for brain, and robot-assisted image-guided cardiovascular and neurovascular interventions. An ideal candidate should have a 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, multi-modality imaging, and image-guided interventions in collaboration with multi-disciplinary team. Interested applicants should send their CV and names of three professional references to Dr. Junghoon Lee [junghoon(at)jhu.edu]. |