The University of Idaho seeks to build on our strength in mathematical, statistical, and computational modeling by adding up to six new tenure-track faculty. We will hire outstanding researchers who use diverse modeling skills to address public health challenges along the continuum from pathogen dynamics at the human-wildlife interface, to emerging disease prediction and prevention, to rural health disparities. Hires will be at the assistant or associate professor level, and research pairs or teams are encouraged to apply. This is a cross-institutional initiative with departmental appointments based on the specialty areas of the successful candidates. Although all types of modeling and data science will be considered, we are particularly interested in individuals with expertise in epidemiology, artificial intelligence / machine learning, molecular modeling, data analytics and visualization, mathematical and statistical modeling, and geospatial modeling.

The successful candidates will have an opportunity affiliate with the Institute for Modeling Collaboration and Innovation (IMCI). IMCI is funded in part by a COBRE grant from the National Institutes of Health and serves as the epicenter for a vibrant research community focused on bringing mathematical, statistical, and computational modeling to collaborative research. Interdisciplinary research is enhanced by regular interactions among researchers with diverse expertise. Current projects are formalized as IMCI Working Groups, which include faculty, research staff, postdocs, and graduate and undergraduate students, usually from multiple disciplines. These grassroots groups create a powerful feedback between modeling, empirical work, and analysis. Successful candidates will have an opportunity to join existing groups or form new groups aligned with their research interests. IMCI also works synergistically with the Institute for Interdisciplinary Data Sciences (IIDS).

U of I is an equal opportunity and affirmative action employer committed to assembling a diverse, broadly trained faculty and staff. Women, minorities, people with disabilities and veterans are strongly encouraged to apply.