A total of four undergraduate fellows will take part in this initiative (ideally two students majoring in the biological sciences and two students majoring in the physical/mathematical sciences or IME). Fellows will be trained in the quantitative and computational methods needed for acquiring, managing, and analyzing large image datasets. These image datasets are used to diagnose, monitor, and guide treatment of diseases ranging from cancer to vascular disease. Potential techniques range from high-intensity focused ultrasound to deep learning for artificial-intelligence driven interpretation of medical images. The development of the skills acquired in this fellowship will serve students well in a variety of subsequent research or career paths.
The fellowship consists of three components: (1) a series of weekly lectures on the basic scientific underpinnings of biomedical imaging technology; (2) a mentored research experience pairing fellows with a faculty mentor; (3) development of a final research report and research presentation with encouragement to submit the research results as abstracts to national meetings. Funding will be available to travel to and attend such meetings.
During the course of the summer, we will arrange for each student to spend a few hours with a clinical radiologist or clinical physicist, depending on their interest, to gain an understanding of the clinical side of biomedical imaging.
Potential projects for summer research, compensation details, and application instructions can be found by following this link to the application site at Handshake.
Application Deadline is April 10, 2019