Postdoctoral Research Scholar - Statistics and Actuarial Sciences

Applications are invited for a one-year postdoctoral scholar position at the University of Iowa, beginning August 15, 2026 and ending August 14, 2027.

The postdoctoral scholar will work as part of a multidisciplinary research team with expertise in statistics, neuroscience, and electrophysiology. The primary responsibility of the position will be to develop new statistical methodologies for analyzing high-dimensional local field potential data generated from electrophysiological experiments in mice. A related objective will be to extend and translate these analytical methods and findings to the study of latent brain networks in humans.

The successful candidate should have demonstrated experience collaborating with neuroscientists and analyzing local field potential data. Responsibilities will include developing new statistical methods for these data, writing computer programs to implement the proposed methods, releasing code as a reproducible software pipeline in Python, conducting simulation studies and real-data analyses, preparing written reports, and participating actively in team meetings. The postdoctoral scholar will be expected to communicate effectively with researchers from diverse disciplinary backgrounds, including biomedical scientists, non-statisticians, and medical professionals.

The postdoctoral scholar will participate in regular meetings with the principal investigators of the project, Drs. Rainbo C. K. Hultman and Hanna Stevens, who lead the Hultman and Stevens Labs in the Carver College of Medicine at the University of Iowa. The scholar will be supervised by Dr. Sanvesh Srivastava in the Department of Statistics and Actuarial Science, who serves as the lead statistician on the project, and will work in close collaboration with members of the Hultman and Stevens Labs.

Ideal candidates will have a strong background in statistics, biostatistics, data science, machine learning, or a related quantitative field, along with substantial experience in computational methods for neuroscience data analysis. Proficiency in Python and experience developing reproducible research software are expected.