NIH NICEATM Postdoctoral Opportunity in AI-Driven Chemical Data Integration and Predictive Toxi[...]

Oak Ridge Institute for Science and Education; Morrisville (NC); On-site; USD 50,000 - 70,000; Full time

Job summary

The Oak Ridge Institute for Science and Education offers a postdoctoral research opportunity focused on developing next-generation Artificial Intelligence and machine-learning approaches for predictive toxicology. The selected participant will gain hands-on experience in curating and integrating chemical and toxicological datasets, benchmarking QSAR models, and applying explainable AI methods.

Located at Keystone Office Park in Morrisville, NC, this role provides a monthly stipend, potential health insurance supplement, and extensive mentorship. The appointment is initially one year, with renewal possibilities for a total of five years.

Qualifications

• Doctoral degree in a relevant field received within the last five years of the appointment start date, or current graduate students nearing completion of the degree.
• Candidate must be 18 years or older at the time of application.
• Open to U.S. citizens, lawful permanent residents, and foreign nationals with eligible immigration status.

Responsibilities

• Learn to curate, integrate, and evaluate heterogeneous chemical and toxicological datasets using FAIR data principles.
• Gain hands-on experience developing and benchmarking QSAR models for regulatory toxicity endpoints.
• Apply explainable AI methods and uncertainty analysis to improve model predictions.

Education

Doctoral degree in a relevant field

Job description

Overview

This postdoctoral research opportunity is currently available within the National Institutes of Health (NIH), National Toxicology Program Interagency Center for the Evaluation of Alternative Toxicological Methods (NICEATM). It focuses on building next‑generation Artificial Intelligence and machine‑learning approaches for predictive toxicology by integrating chemical, toxicological, and biological data into FAIR, interoperable pipelines within the NIH Integrated Chemical Environment (NICE). The participant will explore resources such as NICE, ToxCast/Tox21, and PubChem to develop Quantitative Structure‑Activity Relationship (QSAR), read‑cross, and predictive models relevant to New Approach Methodologies. Emphasis will be placed on interpretability, uncertainty characterization, reproducibility, and transparent model development for regulatory science.

Responsibilities

The participant will learn how to curate, integrate, and evaluate heterogeneous chemical and toxicological datasets using FAIR data principles and reproducible computational workflows. Through mentored research, the participant will gain hands‑on experience developing and benchmarking QSAR, read‑cross, graph neural networks, and transformer‑based models for regulatory‑relevant toxicity endpoints. The participant will also learn to apply explainable AI methods, uncertainty analysis, and domain‑of‑applicability concepts to improve confidence, transparency, and performance for model predictions. Additional learning will include interdisciplinary collaboration, scientific writing and communication, open‑science software development and documentation, and translation of advanced computational approaches into practical decision‑support tools for NAM‑based research and regulatory applications.

Qualifications

• Doctoral degree in a relevant field received within the last five years of the appointment start date, or current graduate students nearing completion of the degree.
• Candidate must be 18 years or older at the time of application.
• Open to U.S. citizens, lawful permanent residents, and foreign nationals with eligible immigration status.

Benefits

Monthly stipend to offset living and other expenses during the appointment. Stipend rates are determined by NIH officials and are based on the candidate’s academic and professional background. NIH may provide a health insurance supplement to cover monthly premium costs if the applicant elects the ORAU/ORISE health insurance plan. The appointment is initially one year and may be renewed, for a total of up to five years. Fellows are expected to be fully engaged in‑person at Keystone Office Park, Morrisville, NC.

Selection Timeline

Initial review of applications will occur on July 1, 2026. Thereafter, applications will be reviewed on a rolling basis throughout the 2026 calendar year, and selections will be made as projects for participation become available.

Nature of Appointment

Participants do not become employees of NIH, DOE, ORISE, or ORAU, and there are no employment‑related benefits beyond those described above.