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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.


Qualifications

  • PhD in ecology, evolution, environmental science, data science, computational biology, epidemiology, computer science, or related field
  • Strong communication skills (oral and written)
  • Collaborative and team-oriented attitude
  • Computational skills (and/or willingness to learn) related to machine learning, mathematical modeling, statistical modeling, and/or geospatial analysis
  • Completion of all doctoral requirements within the last three years and no later than September 1, 2023

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.


Timeline

  • Application Deadline: March 10, 2023 (Applicants advancing in the review process may be asked to submit additional materials, including letters of recommendation, and may be invited to interview.)
  • Selections to be made by mid-April, 2023
  • This is a 1-year appointment starting Fall 2023

Apply

For full consideration, send a complete application in a single PDF to HAI-Fellowships@stanford.edu with the subject line: “HAI Postdoc Fellowship - Mordecai Lab.”

Complete applications will include:

  • Cover letter explaining your interest in becoming a postdoc with the respective research lab/center/faculty through the HAI Postdoctoral Fellowship Program (500 words max).
  • Curriculum Vitae (CV)
  • Short answer responses (300 max each):
    • Description of your dissertation research and broader research agenda
    • How do you see your research training and expertise contributing toward the understanding and advancement of Human-Centered AI? HAI thinks about "Human-Centered AI" through three focus areas.
  • One representative writing sample (published or unpublished)

The expected base pay for this position is $80,000-85,000/yr. The pay offered to the selected candidate will be determined based on factors including (but not limited to) the qualifications of the selected candidate, budget availability, and internal equity.

Stanford is an equal opportunity employer and all qualified applicants will receive consideration without regard to race, color, religion, sex, sexual orientation, gender identity, national origin, disability, veteran status, or any other characteristic protected by law.