Open Rank Professor — Data Science & Society

The University of North Carolina at Chapel Hill; North Carolina; On-site; USD 120,000 - 190,000; Full time

Benefits offered by this job

Comprehensive benefits package

Paid leave

Health, life, and retirement plans

Job summary

The University of North Carolina at Chapel Hill invites applications for an Open Rank Professor in Data Science and Society. The position, housed in the Division within SDIS, focuses on AI/ML, data science foundations, and societal applications across multiple disciplines.

This is a full-time, permanent faculty role with a start date of July 1, 2027. We seek researchers who will contribute to interdisciplinary teaching, supervision, and external funding, advancing data science research and its

Qualifications

• The applicants must have a Ph.D. and/or MD with expertise in artificial intelligence/machine learning, computational social sciences, data science, computer science, statistics, applied mathematics, or a related field that applies AI and data science techniques.

Responsibilities

• Contribute to research in data science foundations, societal impact, and applications across medical, social, physical, biological, and environmental sciences.
• Teach, supervise, and mentor undergraduate, graduate, and professional students in data science and related fields.
• Collaborate across interdisciplinary teams to translate research into societal benefits and engage with external partners.

Skills

Artificial intelligence

Machine learning

Data science

Computational social sciences

Statistics

Applied mathematics

Education

PhD or MD

Job description

The University of North Carolina at Chapel Hill invites applications for an Open Rank Professor in Data Science and Society. The position, housed in the Division within SDIS, focuses on AI/ML, data science foundations, and societal applications across multiple disciplines.

This is a full-time, permanent faculty role with a start date of July 1, 2027. We seek researchers who will contribute to interdisciplinary teaching, supervision, and external funding, advancing data science research and its