FDA Machine Learning Fellowship

Organization
U.S. Food and Drug Administration (FDA)
Reference Code
FDA-CDER-2022-0782
How to Apply

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A complete application consists of:      

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

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

Application Deadline
6/30/2022 3:00:00 PM Eastern Time Zone
Description

*Applications will be reviewed on a rolling-basis.

Multiple opportunities may be available at the U.S. Food and Drug Administration (FDA), Center for Drug Evaluation and Research (CDER) in Silver Spring, Maryland and Stanford University/University of California, San Francisco. The participant will likely spend only a small portion of the time in Silver Spring for project acquaintance, mentor establishment, and familiarity but then will continue the experience at Stanford/UCSF.

The Office of Clinical Pharmacology (OCP) at the FDA is launching an Artificial Intelligence (AI) initiative to support the healthcare applications of this technology as an emerging frontier in regulatory decision making. As part of this initiative, OCP is partnering with the UCSF-Stanford Centers of Excellence in Regulatory Science and Innovation (CERSIs) to offer a one year ORISE opportunity for an interested participant to conduct high impact regulatory science research.

This AI fellowship provides the opportunity for an individual to train in collaboration closely with scientists at both Stanford University/UCSF and the FDA to conduct research that will advance new drug development and promote public health. During participation in this program, the participant will engage in various activities that include but are not limited to the applications of AI/machine learning (ML) for precision medicine, drug development and regulatory science.

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 both at FDA in the Silver Spring, Maryland, area and at Stanford University/UCSF. 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 with completion by the end of May 2022. Degree must have been received within five years of the appointment start date.

Prospective candidates who hold a doctoral degree in computer science or engineering, and are familiar with Artificial Intelligence and Machine Learning are strongly encouraged to apply.

Preferred skills:

  • Strong background in statistics
  • Advanced proficiency in at least one programming language (e.g., Python, R)
  • Excellent analytical skills
  • Profound interest in projects that advance regulatory science and public health
Eligibility Requirements
  • Degree: Master's Degree or Doctoral Degree received within the last 60 months or anticipated to be received by 5/31/2022 11:59:00 PM.
  • Academic Level(s): Postdoctoral or Post-Master's.
  • Discipline(s):
    • Computer, Information, and Data Sciences (16 )
    • Engineering (5 )
    • Environmental and Marine Sciences (1 )
    • Life Health and Medical Sciences (45 )
    • Mathematics and Statistics (11 )
Affirmation

Have you lived in the United States for at least 36 out of the past 60 months? (36 months do not have to be consecutive.)

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