Department or Employer: U.S. Department of Agriculture (USDA)
Location: Beltsville, MD
Contact Info: Lauren.OConnor@usda.gov David.Baer@usda.gov.
Project or Group Web Site: https://www.zintellect.com/Opportunity/Details/USDA-ARS-2022-0164
Position Type: Paid
Availability: Summer
Description:
Research Project: 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.
Learning Objectives: The participant will apply and advance skills in HPC computing technologies and will help develop and co-lead ARS-wide workshops, resulting in a community of scientific practice on using high-dimensional data in which the number of measurements on an individual is orders of magnitude larger than the sample size. An example of this is a dietary intervention of 50 individuals with untargeted metabolomic analysis of urine, blood, and stool resulting in >1000 data points per individual. The participant will have the opportunity to collaborate with multiple USDA ARS scientists on identifying biomarkers of different dietary patterns to be used in reducing measurement error of self-reported dietary data, as well as investigating how dietary patterns influence measured health outcomes such as fasting glucose or the microbiome.
USDA-ARS Contact: If you have questions about the nature of the research, please contact Lauren O’Connor at Lauren.OConnor@usda.gov or David Baer at David.Baer@usda.gov.
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.
Date Posted: 18 Apr 2022