Tenure-Track Assistant or Associate Professor , Business Analytics & Computer Information Systems at Manhattan University – The Bronx, New York

Anticipated start date: August 24, 2026 (pending budget approval for 2026-2027 fiscal year)

The O’Malley School of Business:

The O'Malley School of Business prepares students for rewarding and exceptional careers. Our curriculum combines modern business theory with immersive, real-world practice, providing the skills you need to creatively solve the challenges of tomorrow. As one of only 5% of business schools worldwide accredited by the Association to Advance Collegiate Schools of Business (AACSB), our students are sought after by many top companies, across a broad spectrum of industries.

Position Summary:

The Manhattan University O’Malley School of Business invites qualified candidates to apply for a full-time Tenure-Track Assistant or Associate Professor position in the Business Analytics & Computer Information Systems department.

This is an in-person, on-campus, non-remote position.

• The hired faculty will be qualified to teach in AI and Machine learning at the undergraduate and graduate levels
• Have strong applied computing skills
• Must provide evidence of teaching effectiveness, research accomplishments, and/or relevant work experience
• Applicants should have a strong commitment to excellence in teaching, research, service as well as curricular development
• The successful candidate will be required to teach both undergraduate and graduate courses
• Engage in scholarly activities, and provide ongoing service to the department, school, and University
• Contribute to the development and assessment of curriculum in business analytics and computer information systems.
• Other duties as assigned.

• By the start of the appointment the candidate should possess an earned Ph.D. in a computational area closely related to business analytics and information systems at large
• The hired faculty will be qualified to teach AI, Machine learning and/or advanced statistical methods at the undergraduate and graduate levels and will have strong applied computing skills
• Candidates must provide evidence of teaching effectiveness, research accomplishments, and/or relevant work experience