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Department

Epidemiology or Biostatistics, College of Public Health

Position

Predictive Modeling

Rank

Assistant Professor

Discovery Themes Focus Areas

Translational Data Analytics

Description

We seek an expert in systems-based predictive modeling to join the Data Analytics core and The College of Public Health. Systems-based approaches to predictive modeling move beyond traditional descriptive statistical methods to include knowledge of underlying biological and human systems in development of dynamic analytic models. Such models are then used to predict health outcomes and evaluate policies.

 

Qualifications

The successful candidate will have experience developing and applying methods based on complexity theory to public health outcomes, such as infant mortality, cancer, and chronic disease. Experts in methods such as modeling systems dynamics, network analysis, stochastic agent-based modeling are particularly encouraged to apply. Qualified applicants will have a PhD in a data analytics-related field, such as Biomathematics/Statistics/Biostatistics, Data Science, Bioinformatics, or Computational Biology. Experience in leading large collaborative research projects and mentoring junior faculty preferred.

Application Instructions

Please submit your cover letter, CV, and 5 samples of publications in peer-reviewed journals to the College of Public Health Human Resources office at cph-hr@osu.edu

 

Commitment to Diversity and Inclusion

The Ohio State University is committed to establishing a culturally and intellectually diverse environment, encouraging all members of our learning community to reach their full potential. We are responsive to dual-career families and strongly promote work-life balance to support our community members through a suite of institutionalized policies. We are an NSF ADVANCE Institution and a member of the Ohio/Western Pennsylvania/West Virginia Higher Education Recruitment Consortium (HERC).

All qualified applicants will receive consideration for employment without regard to race, color, religion, sex, sexual orientation, gender identity, national origin, disability status, or protected veteran status.