A postdoctoral researcher position for the development and translation of artificial intelligence (AI) algorithms in medical imaging (Radiology) is available in the Radiomics and Augmented Intelligence Laboratory (RAIL), Department of Radiology and the Norman Fixel Institute for Neurological Diseases, University of Florida College of Medicine, Gainesville, FL, under the supervision of Dr. Reza Forghani (https://xray.ufl.edu/augmented-intelligence/). This position is for an initial one-year appointment, but has the potential to be renewed for an additional year based on performance and funding availability.
The postdoctoral medical AI research fellow will be joining a dynamic team within an academic health center and leading research and development in medical applications of AI in collaboration with different academic groups as well as industry partners. The successful candidate would be expected to take a leadership role under the supervision of the principle investigator(s) in overseeing, designing, and developing algorithms for various AI applications that include but is not limited to the analysis of medical images such as CT and MRI scans. Working as part of a multi-disciplinary team that includes clinicians and scientists and industry partners when appropriate, the medical AI post doc fellow will be participating in and leading the development of AI algorithms that are intended to be clinically impactful, generalizable, and have a high likelihood of being adopted by leveraging the latest technology and clinical domain expertise.
The University of Florida, Gainesville, is one of only a few comprehensive universities, having medical, dental, engineering, computer science, and other major disciplines all co-localized on the same, contiguous campus. The University of Florida is listed as one of the top five public research universities in the United States, with a comprehensive long term AI initiative and availability of state-of-the-art infrastructure that includes a supercomputer. The Shands Hospital/UF Health, Gainesville, is a major referral center for the state of Florida covering a wide range of pathologies and the Norman Fixel Institute for Neurological Diseases has state of the art facilities with an array of advanced imaging and a dynamic multi-disciplinary AI research group.
As a city, Gainesville is located in the northern region of Florida, within 1-1.5 hours of each coast, and just 1.5-2 hours to Orlando and Tampa. It is a dynamic and diverse small to medium-sized city and university town with excellent dining, living, excellent public and private schools, and southern hospitality
- PhD degree in computer science, electrical and computer engineering, biomedical engineering, applied mathematics, medical physics, or related fields
- The successful candidate should have a strong background in machine learning applications including deep learing applications for medical image analysis, computerr vision, and/or data science
- Proficient in Python
- Familiarity with Natural Language Processing would be a bonus
- A strong track record of publications would be an asset
- Excellent written and verbal communication skills
- Ability to work independently and in a team
- Ability to take initiatives, set priorities, time-manage, and resolve problem
|Special Instructions to Applicants:
Please attach your CV, 3 letters of recommendation along with a cover letter detailing your relevant experience and career objectives.
The University of Florida is committed to non-discrimination with respect to race, creed, color, religion, age, disability, sex, sexual orientation, gender identity and expression, marital status, national origin, political opinions or affiliations, genetic information and veteran status in all aspects of employment including recruitment, hiring, promotions, transfers, discipline, terminations, wage and salary administration, benefits, and training.
This is a time limited position.
This requisition has been reposted. Previous applicants are still under consideration and need not apply.
Application must be submitted by 11:55 p.m. (ET) of the posting end date.