Applications are open for Postdoctoral Fellowship at the Massachusetts Institute of Technology in the United States of America. Institute for Medical Engineering and Science (IMES needs the fellow to apply machine learning algorithms to the diagnosis and treatment of cardiovascular diseases, working at the intersection of computer science and medical engineering.

The fellow will lead research within the area of atherosclerotic lesion preparation using quantitative medical image processing to provide novel insights into the mechanisms of the interventional procedure. With access to state-of-the-art clinical image data, pre-clinical research facilities, and direct collaboration with leading industry partners and clinicians, will develop machine-learning algorithm to extract morphological and functional changes imposed by the procedure.

Continuation of the project may also involve the predictive model generation and coupling of image analysis with patient-specific interventional modeling. In addition to unique access to medical images and relevant clinical data, will closely work with a team of medical engineers, clinical interventionists, and relevant industry leaders.

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Requirements

In order to be eligible for this Postdoctoral Fellowship at the Massachusetts Institute of Technology, candidates must have the following qualifications

• A completed Ph.D. degree or its equivalent in computer science, artificial intelligence, biomedical engineering, machine learning, or a related subject.
• Experience developing and testing deep learning networks.
• Demonstrated publication record in journals/conferences.
• Mastery of Python/MATLAB and expertise with at least one deep learning framework (Tensorflow, PyTorch etchellip).
• An interest in medical applications and collaborating with medical professionals.
• Experience in cardiovascular research; and familiarity with state-of-the-art architectures and relevant medical image analysis, particularly intravascular modalities preferred.

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