Postdoctoral positions in PET image reconstruction, analysis, and machine learning￼
The Gordon Center for Medical Imaging (GCMI) in the Department of Radiology at Massachusetts General Hospital (MGH) and Harvard Medical School (HMS) has multiple openings for highly qualified individuals at the postdoctoral level to work with Dr. Kuang Gong on NIH funded projects related to PET image reconstruction, medical image analysis, and machine learning methodologies.
The research projects aim to utilize machine learning-based image reconstruction and analysis to improve the diagnosis and progression tracking of Alzheimer’s disease (AD) and cancer. The projects are based on collaborations with clinicians from MGH, Harvard Aging Brain Study (HABS) and MD Anderson Cancer Center (MDACC). The successful candidate will have joint appointments at MGH and HMS.
- Applicants should have earned a Ph.D. in engineering, statistics, mathematics, physics, neuroscience, or a related field.
- Strong analytical, quantitative, programming and communication skills are essential.
- Prior research experience with image reconstruction or medical image analysis is required.
- Prior research experience with machine learning or deep learning, and proficiency in Pytorch/TensorFlow programming is desirable.
- Applicants should be self-motivated and able to work independently as well as in a collaborative environment.
The Department of Radiology offers extensive core research facilities, including a new digital time-of-flight PET/CT scanner, brain and whole-body PET/MRI scanners, small animal PET/SPECT/CT systems and several MRI scanners, including two 7T ultra-high-field scanners. It also includes a large-scale computing facility for image analysis, network training, tomographic reconstruction, Monte Carlo simulation, and other computationally intensive research applications. The successful applicant can interact collaboratively with a large, growing research group in diverse areas of imaging technology and applications.
The positions are available as of April 2022 and the start date is flexible. If interested, please send your curriculum vitae, a cover letter describing your background and research interests, and contact information of three references to Dr. Kuang Gong (). Applications will be reviewed in a rolling basis until the positions are filled.