Assistant Professor in Statistics and Biostatistics

This early-career hire will focus on foundational statistical and optimization methods for safe and reliable AI, with applications in biomedicine and public health. Duties of this position include teaching, research, and service. The hired candidate will be expected to teach courses at both undergraduate and graduate levels at the intersection of their expertise and the needs of the department.

The departments are seeking candidates with a doctorate (or foreign equivalent) in statistics, biostatistics, operations research, artificial intelligence or a related field. Areas of interest include, but are not limited to, robust and stochastic optimization, generative and foundation models, reliable and robust machine learning, uncertainty quantification, sequential decision-making, and AI systems operating under uncertainty in high-stakes environments. The secondary appointment in Biostatistics will facilitate close collaboration with applied researchers and provide pathways for translating methods into practice.

Candidates are expected to highlight the connection between their research and their application focus in their cover letters.

Screening of applications will begin November 9, 2026, on a rolling basis. Applicants are encouraged to apply by that date to be included in the initial review cycle; applications submitted afterwards will continue to receive full consideration while the position remains open. The application package should include a cover letter, an up-to-date curriculum vitae, research and teaching statements, representative papers, and a list of relevant graduate courses taken.

Applicants should also arrange for four letters of recommendation. At least one of the letters should include an evaluation of the applicant's teaching ability. For inquiries, please contact STOR-Cluster.