Careers

Description:

This postdoctoral position focuses on building computational tools to better understand and predict severe waterborne and foodborne Vibrio infections—a group of pathogens with high mortality rates that are increasing in the United States, yet for which we lack tools to identify which individuals and communities are at greatest risk. The postdoctoral fellow will join the Wiens Lab to work on an NIH-funded project aiming to: 1) Identify sociodemographic, clinical, and environmental risk factors associated with severe Vibrio infection, and 2) Develop a county-level risk stratification tool for severe Vibrio outcomes to guide public health resource allocation. The position includes opportunities to publish lead and co-authored peer-reviewed manuscripts, present findings at scientific meetings, develop independent research projects of mutual interest, and apply for grants (postdoc-initiated and collaborative). Ample opportunities will be available to work with collaborators at Temple University and the CDC.

Responsibilities

● Develop and apply statistical models to vibriosis research questions, including Bayesian hierarchical and predictive machine learning models.

● Assemble, manage, and analyze national patient-level surveillance datasets and county-level sociodemographic and environmental risk factor datasets.

● Visualize model outputs model outputs for partners in academia and public health practice.

● Actively participate in collaborative research meetings.

● Perform additional research-related duties as assigned

Skills/Eligibility:

Qualifications

● Doctoral degree and research experience in epidemiology, biostatistics, public health, or a related quantitative field at time of hire.

● Excellent communication skills, both oral and written.

● Ability to work independently and as part of a team.

● Proficiency in a statistical programming language such as R, Python, or SAS (R preferred).

● Experience or strong interest in learning approaches to assemble, clean, and analyze spatial datasets.

How to Apply:

Submit 1) your CV, 2) a cover letter describing your interest in this position, your qualifications, and your research and career goals, 3) a publication or writing sample, 4) a sample of code written for a previous project, and 5) contact information for three references to Dr. Kirsten E. Wiens (kirsten.wiens@temple.edu) and Dr. Sezgin Ciftci (sezgin.ciftci@temple.edu).

Application review will begin on November 3, 2026, and continue until the position is filled.