美国西北大学招聘医学AI影像方向博士后研究员
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The Department of Radiology at Northwestern University is inviting applications for a Postdoctoral Research Fellow to work on developing scalable AI approaches with applications in multi-modal medical imaging, including PET/CT, PET/MRI, SPECT/CT and other state-of-the-art modalities. The fellow will join a dynamic team of AI scientists and clinicians, participating in unique opportunities to apply AI for both scientific discovery and directly impact patient care in clinical settings.
Responsibilities
- Perform research and development of novel AI algorithms for multi-modal medical imaging applications. Translate research findings in clinical environments, if applicable.
- Work under the supervision of the PI and collaborate with other researcher fellows, clinicians, and students to discuss, develop, and implement research agenda.
- Present work at scientific conferences and publish high quality papers.
Qualifications
- A Ph.D. or equivalent degree in Biomedical Engineering, Computer Science, Medical Physics, Electrical Engineering, or other quantitative related fields. Research background in deep learning and computer vision. Experience in medical image analysis (segmentation/registration/translation) and/or image reconstruction (low-dose/low-count/accelerated acquisition imaging) is a plus.
- At least one first-author high-impact journal or conference (e.g. MedIA, IEEE-TMI, IEEE-TPAMI, IEEE-TRPMS, EJNMMI, CVPR, ICCV, MICCAI, IPMI, etc).
- Proficient in programming languages such as Python, Matlab, and C++. Expertise with one of the deep learning frameworks is a must (e.g., Pytorch, Tensorflow, Keres).
- Highly self-motivated and independent with strong communication skills and excellent scientific writing ability.
Start Date: May-Sep 2024.
Close Date: Until filled.
Visa will be supported by NW for qualified international candidate.
If interested, please email (1) a cover letter outlining your research interests, (2) up-to-date CV, and (3) the contact information of 2 references to Dr. Bo Zhou ([email protected]).
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