SIR to fund medical research fellow

The Society of Interventional Radiology (SIR) Foundation has launched a collaboration to provide funding for one medical student conducting preclinical research in interventional radiology during 2012 and 2013 in the Howard Hughes Medical Institute's (HHMI) Medical Research Fellows Program.

The HHMI Medical Research Fellows Program enables medical, dental and veterinary students from schools in the U.S. to spend a year conducting basic, translational or applied biomedical research full time at any school or nonprofit research institution in the U.S.

HHMI funds up to 66 applicants, and the SIR Foundation's commitment allows for the funding of one high-achieving, medical student engaged in full-time research at the interface of the disciplines of science, medicine and engineering.

The HHMI fellowship application process requires that applicants have selected a solid biomedical research project (either new or ongoing) and established a relationship with a mentor who has strong grant support and a solid training and publications track record. The application deadline is Jan. 11, 2012.

A multilevel evaluation and review process will determine the program's final awardees. Acceptance letters are expected to be sent out in March 2012; the year-long fellowship will begin in the summer of 2012. Students may apply during any year of medical school; however, applicants in the last year of medical school must defer graduation until completion of the fellowship.

 

Around the web

To fully leverage today's radiology IT systems, standardization is a necessity. Steve Rankin, chief strategy officer for Enlitic, explains how artificial intelligence can help.

RBMA President Peter Moffatt discusses declining reimbursement rates, recruiting challenges and the role of artificial intelligence in transforming the industry.

Deepak Bhatt, MD, director of the Mount Sinai Fuster Heart Hospital and principal investigator of the TRANSFORM trial, explains an emerging technique for cardiac screening: combining coronary CT angiography with artificial intelligence for plaque analysis to create an approach similar to mammography.