FDA Artificial Intelligence/Machine Learning Fellowship

Organization
U.S. Food and Drug Administration (FDA)
Reference Code
FDA-OWH-2020-0009
How to Apply

A complete application consists of:      

  • An application
  • Transcripts – Click here for detailed information about acceptable transcripts
  • A current resume/CV, including academic history, employment history, relevant experiences, and publication list
  • A cover letter (please submit in the "Writing Sample" section)
  • Three educational or professional recommendations

All documents must be in English or include an official English translation.

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

Application Deadline
7/1/2020 3:00:00 PM Eastern Time Zone
Description

*Applications will be reviewed on a rolling-basis.

A research opportunity is currently available with the Office of the Commissioner (OC) Office of Women's Health (OWH), U.S. Food and Drug Administration (FDA). The project will be located at the Center for Devices and Radiological Health (CDRH) in Silver Spring, Maryland.

The Division of Imaging, Diagnostics, and Software Reliability (DIDSR) at the Office of Science and Engineering Laboratories (OSEL) in FDA is currently seeking a highly qualified individual to participate in a research project in artificial intelligence/machine learning (AI/ML) applied to digital pathology. Under the guidance of a mentor, the participant will collaborate on a project funded by FDA's Office of Women’s Health (OWH), involving DIDSR staff, associates in other divisions within FDA, and external clinical collaborators (Washington Univ. at St Louis School of Medicine, Univ. of Maryland School of Medicine, Johns Hopkins Hospital) to develop and evaluate AI/ML algorithms linking histological data from whole slide images and related clinical factors to patient outcomes. The selected participant will have a chance to interact with a multidisciplinary group of scientists within the division and to learn about regulatory science issues at the FDA.   

Anticipated Appointment Start Date: September 15, 2020

This program, administered by ORAU through its contract with the U.S. Department of Energy to manage the Oak Ridge Institute for Science and Education, was established through an interagency agreement between DOE and FDA. The initial appointment is for one year, but may be renewed upon recommendation of FDA contingent on the availability of funds. The participant will receive a monthly stipend commensurate with educational level and experience. Proof of health insurance is required for participation in this program. The appointment is full-time at FDA in the Silver Spring, Maryland, area. Participants do not become employees of FDA, DOE or the program administrator, and there are no employment-related benefits.

Completion of a successful background investigation by the Office of Personnel Management is required for an applicant to be on-boarded at FDA.  OPM can complete a background investigation only for individuals, including non-US Citizens, who have resided in the US for a total of three of the past five years.

FDA requires ORISE participants to read and sign their FDA Education and Training Agreement within 30 days of his/her start date, setting forth the conditions and expectations for his/her educational appointment at the agency.  This agreement covers such topics as the following:

  • Non-employee nature of the ORISE appointment;
  • Prohibition on ORISE Fellows performing inherently governmental functions;
  • Obligation of ORISE Fellows to convey all necessary rights to the FDA regarding intellectual property conceived or first reduced to practice during their fellowship;
  • The fact that research materials and laboratory notebooks are the property of the FDA;
  • ORISE fellow’s obligation to protect and not to further disclose or use non-public information.
Qualifications

The qualified candidate should have received a master's or doctoral degree in one of the relevant fields, or be currently pursuing one of the degrees and will reach completion by the appointment start date. Degree must have been received within five years of the appointment start date.

Preferred skills:

  • Proficient in communicating in English
  • Developing and analyzing AI/ML methods (CNN, RNN, GAN, etc.)
  • Programming with languages such as Python (including scientific stack: NumPy, SciPy, scikit-learn, etc.) or C, and deep learning frameworks (TensorFlow, PyTorch, etc.)
  • Experience with image analysis, microscopy, or statistical analysis of diagnostic data
  • Experience with image analysis of histologic whole slide images
Eligibility Requirements
  • Degree: Master's Degree or Doctoral Degree received within the last 60 months or anticipated to be received by 9/15/2020 11:59:00 PM.
  • Discipline(s):
    • Computer, Information, and Data Sciences (7 )
    • Engineering (5 )
    • Life Health and Medical Sciences (1 )
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