USDA-ARS SCINet/AI-COE Postdoctoral Fellowship in AI-Driven Solutions for Food Safety (USDA-ARS-SCINet-2026-0369)

Wyndmoor, Pennsylvania, United States Stipend USD 100,000 - 110,000 per year plus health insurance Fellowship On-site

Postdoctoral fellowship applying machine learning to non-targeted high-resolution mass spectrometry analysis of PFAS in foods, food contact materials and agricultural samples.

Country: United States
Experience: Experience not specified
Salary / stipend: Stipend USD 100,000 - 110,000 per year plus health insurance supplement and relocation support
Application deadline: 04 Dec 2026
Availability: Open

Who can apply

Doctoral degree (received or in progress) in a relevant field

Review the original notice to confirm the requirements. Related degrees are not automatically equivalent; the recruiting organisation decides eligibility.

What you’ll do

Build HRMS databases for PFAS, train and validate machine learning models to identify unknown PFAS, and apply the tools to food safety monitoring, while taking part in SCINet training and science communication.

What the employer asks for

Doctorate in a relevant field; preferred HRMS and non-targeted analysis expertise, R and Python, machine learning model development and a publication record. U.S. citizenship required.

How to apply

Read the full notice and follow the instructions on the original application page.

Application deadline 4 Dec 2026, 3:00 PM Eastern

Source & editorial check

U.S. citizens only. Participants are ORISE fellows, not USDA employees. Mentor: Yelena Sapozhnikova (USDA-ARS). Start expected 2027.

Original posting: 2026-09-11
Checked 2026-11-05 · Updated 2026-11-05