Systems Engineering Teaching Professor

1000scholars; Town of Ithaca (NY); On-site; USD 58,000 - 237,000; Full time

Job summary

Cornell University’s Systems Engineering Program invites applications for an open-rank Teaching Professor position in AI. The candidate will teach three courses annually, advise MEng projects, and help shape graduate education across multiple disciplines.

The role is open-rank (Assistant, Associate, or Full), on-campus, non-tenure-track with long-term renewable appointment, emphasizing teaching quality and curriculum development.

Qualifications

• Candidates must hold a doctoral degree (Ph.D. or equivalent).
• Expertise in artificial intelligence and ability to teach AI within larger engineered systems.

Responsibilities

• Teach three graduate-level courses annually and advise Master of Engineering projects.
• Contribute to curriculum development, advance pedagogical practices, and mentor other educators.

Skills

AI expertise

Teaching

Education

Ph.D. or equivalent

Job description

Position Description

The Cornell Systems Engineering Program is experiencing significant growth, driven by strong recognition through innovative industry collaborations and honors from leading professional societies. AI is increasingly becoming a critical subsystem within engineered products and systems. Systems engineering provides the framework needed to architect, integrate, and manage it within complex systems. To meet this need, we are inviting applications for a new faculty position at the rank of Assistant, Associate or Full Teaching Professor. We seek a candidate with expertise in artificial intelligence who can teach engineers to design, deploy, and oversee AI within larger systems, addressing challenges such as data dependence, model updates, and human–AI interaction. This position offers the opportunity to help shape the future of systems engineering across domains, from energy and infrastructure to biotechnology and healthcare. It's part of a broader effort spanning multiple disciplines and key industry collaborations, including Lockheed Martin, Intel, Arm, and more.

We are especially interested in candidates with expertise in at least one of the following areas:

• Digital twins
• AI-service integration
• Embedded, Edge, and Physical AI systems
• AI security and resilient systems
• AI for infrastructure, energy, and transportation
• AI for biotechnology and life sciences
• Human-AI systems and decision making
• AI4SE & SE4AI

This is an open-rank, full-time, on-campus, non-tenure-track position with a long-term, renewable appointment. The role focuses primarily on teaching three courses and advising Master of Engineering projects annually. Candidates must hold a doctoral degree (Ph.D. or equivalent). Academic ranks of Assistant, Associate, or Full Teaching Professor will be determined based on experience and qualifications. Teaching Professors are expected to deliver high-quality classroom instruction, contribute to curriculum development, advance pedagogical practices, and mentor other educators. Initial appointments are for up to three years for Assistant Teaching Professors and up to five years for Associate and Full Teaching Professors.

The Systems Engineering Program at Cornell builds upon the broad expertise of its faculty to deliver unique, transdisciplinary master’s and doctoral education. It attracts a diverse cohort of students from multiple disciplines, industries, and countries. The faculty member appointed to this position will play a pivotal role in shaping the future of the program and will actively participate in strategic planning and operational decisions. As a core member of the Systems faculty, the successful candidate is expected to contribute to the program’s educational mission by teaching a select number of well-established, analytically focused graduate-level courses; ensuring course content remains current and relevant by engaging with ongoing research in Systems; and advising graduate students on systems-related projects.

Pay Ranges

$58,300 - $237,300

The hiring rate of pay for the successful candidate will be determined considering the following criteria:

• Prior relevant work or industry experience.
• Education level to the extent education is relevant to the position.
• Academic Discipline (faculty pay ranges reflects 9-month annual salary)
• Unique applicable skills.

More details or general questions about the position can be found by emailing Gurpreet Kaur, the Systems Engineering Director's Assistant at [e-mail].

EEO Statement

Cornell welcomes students, faculty, and staff with diverse backgrounds from across the globe to pursue world-class education and career opportunities, to further the founding principle of "... any person ... any study." No person shall be denied employment on the basis of any legally protected status or subjected to prohibited discrimination involving, but not limited to, such factors as race, ethnic or national origin, citizenship and immigration status, color, sex, pregnancy or pregnancy-related conditions, age, creed, religion, actual or perceived disability (including persons associated with such a person), arrest and/or conviction record, military or veteran status, sexual orientation, gender expression and/or identity, an individual's genetic information, domestic violence victim status, familial status, marital status, or any other characteristic protected by applicable federal, state, or local law.

Cornell University embraces diversity in its workforce and seeks job candidates who will contribute to a climate that supports students, faculty, and staff of all identities and backgrounds. We hire based on merit, and encourage people from historically underrepresented and/or marginalized identities to apply. Consistent with federal law, Cornell engages in affirmative action in employment for qualified protected veterans as defined in the Vietnam Era Veterans' Readjustment Assistance Act (VEVRRA) and qualified individuals with disabilities under Section 503 of the Rehabilitation Act. We also recognize a lawful preference in employment practices for Native Americans living on or near Indian reservations in accordance with applicable law.