Tenure-Track AI for Advanced Manufacturing Innovation

IISE International; Columbus (OH); On-site; USD 90,000 - 130,000; Full time

Job summary

The Ohio State University in Columbus, OH invites applications for a Tenure Track Assistant Professor in AI applications in advanced manufacturing. The joint appointment spans the Department of Integrated Systems Engineering and the Department of Mechanical and Aerospace Engineering, with a target start as early as Fall 2027.

The successful candidate will develop AI methods to monitor, optimize, or automate manufacturing processes, pursue external funding, and contribute to teaching at both

Qualifications

• AI/ML expertise demonstrated through scholarly work and applications to manufacturing.
• Strong research record in AI/ML with relevance to manufacturing processes or systems.
• Experience collaborating across disciplines with engineering and industry partners.
• Ability to secure funding and manage research collaborations.
• Excellent communication and mentoring skills for students and junior researchers.

Responsibilities

• Develop and pursue a funded research program in AI applications for advanced manufacturing.
• Contribute to undergraduate and graduate teaching in AI/ML methods and intelligent manufacturing systems.
• Publish in peer‑reviewed venues and participate in national/international service.
• Collaborate with MAE and ISE faculty on interdisciplinary projects and curricula.
• Mentor students and build partnerships with industry and other external stakeholders.

Skills

AI/ML expertise

Manufacturing systems

Interdisciplinary collaboration

Grant development

Education

Ph.D. in Industrial & Systems Engineering or related

Job description

The Ohio State University in Columbus, OH invites applications for a Tenure Track Assistant Professor in AI applications in advanced manufacturing. The joint appointment spans the Department of Integrated Systems Engineering and the Department of Mechanical and Aerospace Engineering, with a target start as early as Fall 2027.

The successful candidate will develop AI methods to monitor, optimize, or automate manufacturing processes, pursue external funding, and contribute to teaching at both