Postdoctoral Fellow (NIEHS)

Over the past 30 years, The National Toxicology Program has generated extensive in vitro and in vivo toxicology datasets. By leveraging these rich resources, our group is now developing deep learning models for toxicology applications, including pathology data from whole-slide images (WSIs), pathology reports, and data from chronic and subchronic animal studies.

Furthermore, our group has developed a foundation model, Tox21mer, for the Tox21 bioassay data, and a resulting manuscript describing this model is expected to be submitted for publication soon. Prospective postdoctoral fellows will build on this work, as we are currently developing a deep learning distillation model that uses Tox21mer to predict outcomes in external chemical bioassays.

Interested applicants must have a doctoral degree in computer science, electrical engineering, mathematics, statistics, or a related area, and fewer than five years of postdoctoral research experience. Candidates with experience in deep learning, foundation models, and/or toxicology are strongly encouraged to apply.

U.S. citizens and permanent residents are eligible to apply. NIH welcomes foreign nationals with the exception of individuals from this list.