Professor (All Ranks) in Embodied AI and Learning-Enabled Autonomy

Arizona State University; Tempe (AZ); On-site; USD 110,000 - 170,000; Full time

Job summary

Arizona State University’s Ira A. Fulton Schools of Engineering and the School of Electrical, Computer and Energy Engineering invite applications for a tenure-track or tenured faculty position in embodied AI and learning-enabled autonomy for physical systems.

The work emphasizes AI systems that perceive, reason, learn, and act with sensors, actuators, humans, and dynamic environments. The appointment at assistant, associate, or full professor rank will begin August 2027, with opportunities

Qualifications

• PhD in electrical engineering, computer engineering, computer science, robotics, or closely related discipline by appointment.
• Evidence of excellence in research and teaching as appropriate to rank.
• Demonstrated potential for external funding and interdisciplinary collaboration.

Responsibilities

• Develop and maintain an internationally recognized, externally funded research program.
• Deliver undergraduate and graduate courses in ASE-related engineering topics.
• Advise and mentor graduate students and engage in service activities.

Skills

Robot learning

AI/ML expertise

Education

PhD in EE/CS/Robotics

Job description

The Ira A. Fulton Schools of Engineering at Arizona State University (ASU) and the School of Electrical, Computer and Energy Engineering seek applicants for a tenure-track or tenured faculty position in the area of embodied AI and learning-enabled autonomy for physical systems. The School of Electrical, Computer and Energy Engineering (https://ecee.engineering.asu.edu/), one of the eight Fulton Schools of Engineering, houses a vibrant electrical engineering research community (learn more at https://research.engineering.asu.edu/). We seek applicants who can enhance our abilities in these areas as part of a community of experts. This position focuses on AI systems that perceive, reason, learn, act, and adapt in the physical world through interactions with sensors, actuators, humans, and dynamic environments. Particular areas of interest include, but are not limited to: novel edge-computing architectures and systems for embodied AI, robot learning, learning-enabled control, multimodal perception, sensor fusion, simulation-to-real transfer, safe reinforcement learning, planning and decision-making under uncertainty, distributed autonomy, and human-autonomy interaction. Application domains may include robotics, autonomous vehicles, humanoids, aerial and space systems, medical and assistive technologies, smart manufacturing, infrastructure monitoring, and defense-relevant autonomous systems.

We search for applicants who will contribute to our academic programs, promote transdisciplinary teaching and research, and help the university to achieve its aspirations, including enabling student success, transforming society, valuing entrepreneurship, and conducting use-inspired research. Faculty members in the Fulton Schools are expected to develop an internationally recognized and externally funded research program, adopt effective pedagogical practices in the development and delivery of undergraduate and graduate courses, advise both undergraduate and graduate student research and projects, and undertake service activities.

The School of Electrical, Computer and Energy Engineering’s research areas reflect the breadth of the electrical engineering profession and our faculty’s expertise, ranging from the smallest nanoelectronics to the U.S. power grid and its control. Graduate students are involved in all of our research activities and have access to state-of- the-art facilities, such as the NanoFab microelectronics fabrication space on the ASU Tempe campus and the MacroTechnology Works facility, a former semiconductor plant converted to lab and prototyping space. Six primary areas of specialization are control systems; electric power and energy systems; electromagnetics, antennas and microwaves; electronics and mixed-signal design; physical electronics and photonics; and signal processing and communications.

In addition, new faculty hired through this search may find exciting opportunities to participate in the activities of the Southwest Advanced Prototyping (SWAP) Hub. Led by ASU, the SWAP Hub is one of eight regional innovation hubs established under the Department of War’s Microelectronics Commons, a national strategic initiative to accelerate the development and production of microelectronics technologies that are critical to U.S. security and defense. With over 200 partners, the SWAP Hub provides unprecedented opportunities for large-scale collaboration to advance microelectronics prototyping and lab-to-fab transition. ASU is also leading the SHIELD USA project in materials and substrates for advanced packaging through the National Advanced Packaging Manufacturing Program. The Materials-to-Fab (MTF) Center, a collaboration with Applied Materials, features upgraded infrastructure to support state-of-the-art semiconductor tools, making ASU one of the few U.S. universities with access to leading-edge equipment for research, workforce development, and government-backed prototyping initiatives. MTF combines Applied Materials’ leadership in materials engineering with ASU’s multidisciplinary R&D expertise, creating a model that accelerates the transfer of innovations from ideation to fab prototype. New faculty will also join a large cross-school robotics and autonomous systems community spanning the Fulton Schools.

Appointment will be at the assistant, associate, or (full) professor rank, commensurate with the candidate’s experience and accomplishments, beginning August 2027.

Essential Functions

• Contribute to curriculum development.
• Deliver instruction in-person and/or online.
• Supervise honors, master’s, and doctoral students.
• Conduct research publishable in top-tier journals and/or conferences in the discipline.
• Develop grant proposals for external funding as PI or co-PI.
• Participate in professional and internal service.

Required Qualifications

• Earned a doctorate in electrical engineering, computer engineering, computer science, robotics, mechanical engineering, or a closely related discipline by the time of appointment.
• Evidence of excellence in research, as appropriate to the candidate’s rank.
• Evidence of excellence in teaching, as appropriate to the candidate’s rank.

Desired Qualifications

• Demonstrated commitment to a collaborative, transdisciplinary approach to research and teaching.
• Record of acquiring external funding.
• Record of impactful publications in top-tier journals/conferences.
• Experience developing and deploying learning-enabled systems on physical platforms such as robots, vehicles, or other cyber-physical systems.
• Commitment to mentoring students and delivering courses in multiple technology-enhanced formats.
• Commitment to innovative pedagogy.
• A demonstrated appreciation for entrepreneurial activities.