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  • Assistant, Associate or Full Professor, Aerospace and Mechanical Engineering
    Aerospace and Mechanical Engineering
    University of Arizona

    The Aerospace and Mechanical Engineer Department (AME) at the University of Arizona invites applications and nominations for a tenure -track faculty position at the Assistant, Associate, or Full Professor level in the area of Machine Learning (ML) and Artificial Intelligence (AI) with an emphasis in control systems and autonomous aerospace and mechanical systems.

    The successful candidate is expected to teach courses at the graduate and undergraduate levels, contribute to mentoring students, and establish an active, externally funded and nationally/internationally recognized research program that is aligned with Grand Challenges of the University of Arizona’s new strategic plan, including intelligent systems, network science, and space technologies. The leveraging of opportunities for synergy with existing research activities in the department, College and the University, as well as an experimental component to the research program, will be viewed favorably.

    The Department offers excellent opportunities to collaborate with ongoing related research efforts in aerodynamics (including Hypersonics), control systems, unmanned aerial vehicles, and spacecraft GNC, micro-technology, rocket and space engineering, as well as other ongoing research efforts in astrodynamics, vibrations, CFD, computational optimization of engineering design, fluid instability, and multi-scale mechanics of materials, and robotics.

    Further opportunities for collaboration on campus include the Department of Planetary Sciences, the Arizona Health Sciences Center, and the Bio5 Institute for Collaborative Bioresearch, the College of Optical Sciences and the Program in Applied Mathematics, all of which enjoy international recognition as centers for world-class academic programs and research.

    Minimum requirements include PhD in Aerospace or Mechanical Engineering or a closely related discipline; demonstrated research potential or accomplishments; experience teaching and mentoring students; research experience; track record of peer-reviewed publications. The selected candidate will be required to provide higher education credentials during the offer discussions.

    Preferred qualifications include a strong track record of peer-reviewed publications; evidence of interdisciplinary collaboration; and previous teaching experience; experience in robotic control; experience with real-time algorithm development; experience with flight dynamics; experience in experimental implementation.

    Full details and application information available online at:

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