FDA Computational Biology and Pharmacology Fellowship

Oak Ridge Institute for Science and Education; Silver Spring (MD); On-site; USD 33,480 - 50,220; Full time

Job summary

The Oak Ridge Institute for Science and Education is seeking candidates for a project involving the development of toxicology databases and computational models. Under mentorship, candidates will analyze data and develop models integrating machine learning and statistical analysis to translate nonclinical data into safety endpoints.

This full-time, renewable one-year position begins around July 1, 2026, with a stipend based on educational level. Eligible applicants must be U.S. citizens, Lawful Permanent Residents, or meet specific immigration guidelines.

Qualifications

• Currently pursuing or have received a master’s or doctoral degree in a relevant field within the last five years.
• Strong background in computational modeling and data analysis.
• Experience with statistical methods and machine learning is preferred.

Responsibilities

• Collaborate with multidisciplinary teams to curate large-scale datasets.
• Investigate patterns in toxicological data using statistical methods.
• Develop AI, statistical, or mechanistic models for safety endpoints.

Skills

Computational modeling

Data analysis

Statistical methods

Machine learning

AI approaches

Communication skills

Education

Master’s or doctoral degree in a relevant field

Job description

About the Opportunity

Under the guidance of a mentor, you will help develop comprehensive toxicology databases and computational models by analyzing proprietary data from drug applications and public literature. The focus is on endpoints where New Approach Methodologies (NAMs) can provide significant regulatory value, integrating machine learning, statistical analysis, and mechanistic modeling to translate nonclinical data into safety endpoints such as cardiotoxicity and immunogenicity.

Responsibilities

• Collaborate with multidisciplinary teams to curate large‑scale datasets.
• Investigate patterns in toxicological data using statistical methods.
• Contribute to the development of reference compound libraries for predictive model validation.
• Develop AI, statistical, or mechanistic models to translate nonclinical data into safety endpoints.
• Participate in stakeholder engagement activities with industry and academic partners.
• Maintain data management systems and quality control procedures.

Required Qualifications

• Currently pursuing or have received a master’s or doctoral degree in a relevant field within the last five years or anticipated to be received by 10/31/2026.
• Strong background in computational modeling, data analysis, or related scientific discipline.
• Experience with statistical methods, machine learning, or AI approaches is preferred.
• Excellent written and verbal communication skills.

Eligibility & Citizenship

This opportunity is available to U.S. citizens, Lawful Permanent Residents (LPR), and foreign nationals who meet the eligibility criteria. Non‑U.S. citizen applicants should refer to program guidelines for valid immigration statuses.

Appointment Details

• Anticipated start date: July 1, 2026 (flexible).
• Duration: One year, renewable upon recommendation and funding availability.
• Location: White Oak, Maryland.
• Full‑time position.
• Stipend: Monthly stipend commensurate with educational level and experience.
• Participants are not employees of FDA, DOE, or ORAU and receive no employment‑related benefits.

Mentor

Zhihua Li ([e-mail])