Description

This early career hire will focus on foundational statistical and optimization methods for safe and reliable AI, with applications in biomedicine and public health. 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. 

Primary responsibilities of the position will include high-quality research, publishing in peer-reviewed journals and broader dissemination, seeking external funding for research, teaching undergraduate and graduate courses, contributing to research mentoring of doctoral students, and engaging in departmental, university, and professional service activities.

Requirements

The departments are seeking candidates with a doctorate (or foreign equivalent) in statistics, biostatistics, operations research, artificial intelligence or a related field.

This position is part of a cluster hire on Safeguarding Artificial Intelligence in Health: Foundations, Uncertainty, and High Stakes Decision Making, at the University of North Carolina at Chapel Hill that involves three jointly appointed positions with the Department of Biostatistics and the Department of Computer Science. This is structured to strengthen collaboration across these departments. The ideal candidate will have research and/or teaching interests that make substantive connections with related fields and would be excited to engage in cross-disciplinary conversations and collaborations.