FDA Digital Pathology Image Analysis Fellowship

About the role

Selected participants will join research projects focused on the development of methods and tools in support of our regulatory science efforts in evaluating computational pathology (CPATH) devices. As a fellow, you will have the opportunity to learn about the assessment of artificial intelligence models applied to whole slide images, with a focus on CPATH imaging AI pipeline and cutting-edge technologies such as vision and language foundation models in segmentation/classification/quantification/chatbot tasks.

Responsibilities

• Develop comprehensive expertise in evaluating artificial intelligence algorithms applied to whole slide images, including understanding performance metrics and validation framework
• Gain proficiency in imaging AI pipeline development and optimization
• Acquire hands-on experience in designing, implementing, and optimizing computational pathology workflows from image acquisition through analysis output with understanding pre-processing techniques
• Learn about cutting-edge vision and language foundation models for pathology applications, including their implementation in segmentation, classification, quantification, and conversational AI tasks

Requirements

The qualified candidate should have received a master's or doctoral degree in one of the relevant fields (e.g., Biomedical Engineering, Computer Science) with preferred research experience in artificial intelligence and digital pathology whole slide image analysis. Degree must have been received within the past five years. Candidates with research experience in artificial intelligence and digital pathology whole slide image analysis are encouraged to apply.

Qualifications

• The candidate should have a master's or doctoral degree in Computer, Information, and Data Sciences, Life Health and Medical Sciences, Mathematics and Statistics, or Physics
• Preferred research experience in artificial intelligence and digital pathology whole slide image analysis

Skills

• Python programming
• Pathology whole slide image analysis
• Machine learning, especially generative adversarial networks
• Oral presentations and writing research papers

Benefits

No specific benefits are mentioned in the job posting.

Pay

The participant will receive a monthly stipend commensurate with educational level and experience.

Schedule

The appointment will initially be for one year, but may be renewed upon recommendation of FDA and is contingent on the availability of funds.

Contact

If you have questions, send an email to ORISE.FDA.CDRH@orau.org. Please include the reference code for this opportunity in your email.

Point of Contact

Ashley