USDA Announces Fellowship for Developing AI and ML Techniques to Advance Understanding of How Dietary Patterns Influence Human Health

Posted on April 22, 2022
USDA Announces Fellowship for Developing AI and ML Techniques to Advance Understanding of How Dietary Patterns Influence Human Health
Position Title                                                                                                                                     506017_1650478508826_USDALogo
Position Summary
Under the guidance of a mentor, the fellow will have the opportunity to gain experience in and learn about the challenges of investigating dietary patterns and human health to develop new methodological machine learning approaches. The fellow will be housed in the Food Components and Health Lab at the Beltsville, MD Human Nutrition Research Center, but will also work closely with the Food Surveys Research Group and Methods and Applications of Food Composition Lab. These three units consist of food chemists, nutritionists, and physiologists with extensive expertise in assessing dietary patterns, dietary assessment, food intake, food composition, public health, and human health outcomes. Our Center has rich dietary datasets collected using methods which provide a daily detailed snapshot of dietary intake and behavioral patterns, which include details at the food level and contextual information about eating events. We also have measured markers of food intake and dietary patterns from urine, blood, and feces of research participants within these datasets which can be used for multiple -omics applications for markers of food intake and metabolism, including microbiome, metabolomics, and genomics. The high dimensionality and complexity of all this information combined outpaces standard statistical applications, thus are ripe for Artificial Intelligence (AI) and Machine Learning (ML) techniques to advance the understanding of how dietary patterns influence different aspects of human health.
How to Apply
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A complete application consists of:
  • An application
  • Transcript(s) – For this opportunity, an unofficial transcript or copy of the student academic records printed by the applicant or by academic advisors from internal institution systems may be submitted. All transcripts must be in English or include an official English translation. Click here for detailed information about acceptable transcripts.
  • A current resume/CV, including academic history, employment history, relevant experiences, and publication list
  • Two educational or professional recommendations
    All documents must be in English or include an official English translation.

Application Deadline
5/31/2022 3:00:00 PM Eastern Time Zone

*Applications will be reviewed on a rolling-basis and this posting could close before the deadline.

USDA-ARS Contact: If you have questions about the nature of the research, please contact Lauren O’Connor at or David Baer at

Anticipated Appointment Start Date: June 2022. Start date is flexible and will depend on a variety of factors.
Appointment Length: The appointment will initially be for one year, but may be renewed upon recommendation of the mentor and ARS, and is contingent on the availability of funds.
Level of Participation: The appointment is full-time.
Participant Stipend: The participant(s) will receive a monthly stipend commensurate with educational level and experience.
Citizenship Requirements: This opportunity is available to U.S. citizens, Lawful Permanent Residents (LPR), and foreign
nationals. Non-U.S. citizen applicants should refer to the Guidelines for Non-U.S. Citizens Details page of the program website for information about the valid immigration statuses that are acceptable for program participation.
ORISE Information: This program, administered by ORAU through its contract with the U.S. Department of Energy (DOE) to manage the Oak Ridge Institute for Science and Education (ORISE), was established through an interagency agreement between DOE and ARS. Participants do not become employees of USDA, ARS, DOE or the program administrator, and there are no employment-related benefits. Proof of health insurance is required for participation in this program. Health insurance can be obtained through ORISE.
Questions: Please visit our Program Website. If you have additional questions about the application process please email and include the reference code for this opportunity.
The qualified candidate should be currently pursuing or have received a master's or doctoral degree in one of the relevant
fields. Doctoral degree candidates are preferred.
Preferred skills:
  • Expertise in modeling high-dimensional data such as metabolomics, genomics, or microbiomics
  • Expertise in applying and developing machine learning methods to high-dimensional data
  • A public health research focus, ideally specific to food and nutrition, but other research areas (physical activity, air pollution, or
    other behavioral public health concerns) will be considered
  • Experience working with data from human research participants
  • Efficient in computer programming languages, including R
  • Strong oral and written communication skills
  • Experience publishing research findings in peer-reviewed scientific journals