Tenure-Track Assistant or Associate Professor , Business Analytics & Computer Information Systems
Job Details
Position Description
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.
Job Responsibilities
- 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.
Requirements
- 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
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