HAI Postdoctoral Fellowship at Mordecai Lab, Department of Biology
Mordecai Lab focuses on the ecology of infectious disease. We are interested in how climate, species interactions, and global change drive infectious disease dynamics in humans and natural ecosystems. This research combines mathematical modeling and empirical work.

The postdoctoral fellow will develop new methods of using AI to study the relationship between environmental change and infectious disease; for example, to quantify land use and its relationship to disease incidence from satellite imagery; to identify genomic variation associated with pathogen infectivity and with evolution of thermal tolerance on mosquito vectors; and to forecast disease incidence in a range of (re)emerging infectious diseases. For example, the postdoc could use genome sequences to model protein structures and protein – protein interactions to understand how the molecular biology of vector – parasite interactions combines with their ecology to determine disease transmission. The postdoc could also develop algorithms to quantify land use change in real-time using daily Planet Labs satellite imagery, matching them with disease surveillance data from both traditional sources (e.g., health surveillance programs) and novel sources (e.g., Google Trends and social media) to identify the risk of zoonotic disease spillover and epidemics.

The postdoc will be a member of the Mordecai Lab in the Biology Department . Their primary mentor will be Erin Mordecai , and they will be encouraged to pursue additional collaborations and mentorship at HAI, within Stanford, and beyond.
Stanford HAI is also committed to creating a diverse community of scholars who are engaged in contributing to the understanding and advancement of Human-Centered AI. Postdoctoral fellows will have the opportunity to engage with one another and with the broader Stanford HAI research community. They are also expected to participate in professional development, cohort-building, and other programmatic activities organized by HAI.

Evaluation Criteria
Candidates will be evaluated based on their fit to the position, enthusiasm for the research questions, and past research accomplishments (including publications and presentations), as well as evidence of their contributions to their current research communities.