Positions Available!

Last updated September 2022

The Cobey Lab is currently seeking several computational techs, postdocs, and PhD-level computational research scientists (as potentially permanent staff) to study the development of immunity to influenza and SARS-CoV-2 after infection and vaccination, the effects of this immunity on viral transmission and evolution, and methods to forecast viral evolution and epidemiology. Researchers will work closely with our collaborators in immunology, virology, and epidemiology and will have ample opportunities to develop new methods and theory and propose new projects. These positions involve leadership opportunities and some great collaborations:

  • a NIH-funded clinical trial (ClinicalTrials.gov NCT04576377) to study the effects of repeated influenza vaccination and develop predictive models of antibody specificity (with Ben Cowling and Nancy Leung, University of Hong Kong; Sophie Valkenburg, Doherty Institute/U. Melbourne; John Tsang, Yale; Scott Hensley, Penn; and Patrick Wilson, Cornell);
  • a R01 to study infection risk and immunity to influenza in childhood (with Aubree Gordon, University of Michigan);
  • another R01 to study heterogeneity in protection to influenza after infection and vaccination (with Ben Cowling, Hong Kong University, and John Tsang, Yale);
  • NIH-funded Collaborative Influenza Vaccine Innovation Center (CIVICs), for which we are investigating the impact of immune history on the immunogenicity and effectiveness of universal and seasonal influenza vaccines (with Florian Krammer, Rafi Ahmed, and other investigators, and the US Influenza Vaccine Effectiveness Network and US CDC);
  • a new NIH Center for Excellence in Influenza Research and Response (Penn-CEIRR) to study influenza and other respiratory pathogens affecting influenza. We are working on models of longitudinal risk and immunity (with Emily Martin and Arnold Monto, University of Michigan) and are leading with Jesse Bloom (Fred Hutch) a project to forecast the epidemiology and evolution of influenza, including influenza vaccine effectiveness (collaborators include Trevor Bedford, Fred Hutch; Scott Hensley, Penn; and Adam Lauring, University of Michigan). This work will include study of other respiratory pathogens.
  • For CEIRR, we are also leading the Computational Modeling Core. The core will integrate models and forecasts, perform model comparisons, launch computational tools, containerize and test software, streamline pipelines, provide tutorials and instruction, and synthesize findings within and beyond the CEIRR consortium.

All of this work supports our lab's central questions: How does immune selection shape pathogen populations, and what does this imply for vaccination strategies? Generally, we are interested in developing predictive models or identifying the limits of prediction. Some of our work is not "applied," e.g., we are also studying how pathogens have shaped the evolution of adaptive immunity and the resulting evolutionary constraints on the B cell response.

Please see our lab handbook for information on lab culture and expectations. Remote working arrangements are possible. We pay a competitive salary and especially welcome members of underrepresented groups.

Successful applicants for the research positions will have strong quantitative skills and a record of productive research. Researchers will have a PhD in a relevant field (e.g., applied math, computer science, ecology and evolution, epidemiology, physics, statistics) or will be on track to obtain one before joining the lab. A PhD is not necessary for all positions, but commitment to learning relevant science is expected. Applicants must have strong written and oral communication skills and commitment to working as part of a constructive, productive, multidisciplinary team.

To apply, please email a cover letter describing your relevant background and interests, CV, contact information for three references, and (for PhD-level scientists/postdocs) two or three relevant publications/preprints to Sarah Cobey at cobey@uchicago.edu. She will direct you to the appropriate job ad (JR17343 or JR18067).

Application review will continue until the positions are filled.