Computational science at the interface between infection, immune response, and public health interventions for low-resource settings

The Francis I. Proctor Foundation at the University of California, San Francisco is seeking a postdoctoral fellow to contribute to seroepidemiologic studies of trachoma, enteric pathogens, and other infectious diseases. The NIH-funded position will focus on computational research in close collaboration colleagues at UC Berkeley, University of Washington, University of Michigan, and the US Centers for Disease Control and Prevention.

The postdoctoral scholar will work closely with Dr. Benjamin Arnold to study infectious disease transmission through antibodies measured in blood. We have multiple NIH R01 grants starting this year to conduct foundational studies that characterize antibody response vis-à-vis infection for diverse pathogens in longitudinal cohorts. We also aim to advance the use of serology to target and monitor infectious disease control programs through spatially informed designs. A theme that spans our work is to take an integrated view across pathogens that span taxa, through the use of high-throughput, multiplex assays and generalizable analysis methods.

The postdoc will join an exceptional team at Proctor, with latitude to lead seroepidemiologic analyses at the intersection of disease elimination, randomized interventions, integrated serological surveillance, and the interplay between infection and immunity. Extensions of the research to pathogens beyond enterics and trachoma, such as malaria and vaccine preventable diseases is both possible and encouraged. The new member of our team will connect into a broad academic network that includes colleagues in the Proctor Foundation (5 other postdocs, currently), UC Berkeley epidemiology/biostatistics, UCSF’s EPPICenter (, and the NTD modeling consortium (

Ideal applicants will have a PhD and a record of achievement in infectious disease epidemiology, biostatistics, bioinformatics, or quantitative biological fields. Applicants must have strong writing and analytical skills, should be adept at programming and data analysis (preferably R), and should have publication record commensurate with experience. Applicants who are interested in global health and who have experience in geostatistical modelling approaches, bioinformatics pipelines, and/or high dimensional data will be a good match. Applicants without experience in these specific areas but who have strong computational skills and an interest in them should apply. Experience with causal inference methods (e.g., DAGs, structural causal models), and transparent/ reproducible data science tools (e.g., GitHub, R markdown) would be helpful to integrate quickly into our team’s workflow.

This position is located at UCSF in San Francisco (, and is available beginning in June, 2021 (start date negotiable). We will review applications on a rolling basis with a first review May 1, 2021. We are dedicated to mentoring and supporting our postdocs so they succeed in their academic career.

UCSF seeks candidates whose experience, teaching, research, or community service has prepared them to contribute to our commitment to diversity and excellence. The University of California is an Equal Opportunity/Affirmative Action Employer. All qualified applicants will receive consideration for employment without regard to race, color, religion, sex, sexual orientation, gender identity, national origin, disability, age or protected veteran status.

Interested applicants should submit a curriculum vitae, a 1-2 page letter that describes their scientific contributions to date and interest in the above areas of research, and contact information for three references, to Dr. Ben Arnold Specific questions regarding this position can be addressed to Dr. Arnold as well.

University of California, San Francisco
San Francisco
Closing date
May 1st, 2021
Posted on
April 1st, 2021 00:27
Last updated
April 1st, 2021 00:27