Minimum Qualifications Applicants must have an earned Ph.D. in Mechanical Engineering or a related field from an accredited university (at least conferred before the start date of September 1, 2024). Prospective candidates in all mechanical engineering areas are strongly encouraged to apply. Preferred Qualifications Priority will be accorded to applicants possessing expertise in Artificial Intelligence and/or Machine Learning as applied to the field of mechanical engineering. For this position, prior postdoctoral research experience is preferred. Strong communication skills and the capacity to collaborate effectively within a team are also highly desirable. Additional preferred qualification include: 1) experience and/or demonstrated ability developing and teaching courses integrating machine learning, artificial intelligence, data science, and/or intelligent engineering systems within the context of mechanical engineering applications, 2) experience and/or demonstrated ability to lead and propose new research projects and proposals to attract external federal, state, or private funding, such as NSF, DoD, DOE, DARPA, NIH, USDOT, NASA, or others, 3) experience and/or demonstrated ability teaching courses in dynamic systems, modeling of physical systems, and control systems, (4) experience and/or demonstrated ability working with undergraduate and graduate engineering students, and (5) demonstrated ability to play a collaborative role as a team member in initiatives for partnerships with schools, community colleges, government agencies, and industry to create an eco-system that will bring economic prosperity to the Rio Grande Valley.