AI and Machine Learning Assistant Professor/Professional Practice Assistant Professor

Overview

Utah State University’s Department of Electrical and Computer Engineering (ECE) invites applications to fill two faculty positions in Artificial Intelligence and Machine Learning (AI/ML): one tenure-track position (research and teaching) and one professional practice position (teaching emphasis). It is expected that these positions will be filled at either the Assistant or Associate Professor level. We seek applicants with cross-disciplinary backgrounds whose expertise lies at the intersection of AI/ML and electrical engineering.  Preference will be given to applicants whose research and/or work experience applies AI/ML to problems in electrical engineering including but not limited to:

• Signal processing, communications, radar
• Control, robotics, drones/UAVs
• Electromagnetics, antennas
• Speech and natural language processing
• Remote sensing, computer vision
• Electric power systems
• Cybersecurity, computer networks, cryptography

The search committee will begin reviewing applications on November 1, 2024, and continue until the position is filled. Possible start dates, coinciding with USU’s semester schedule, are January 2025 and August 2025.

Responsibilities

Successful candidates for the tenure-track position will be expected to develop an externally funded research program that includes peer-reviewed publications and graduate student mentorship. Both tenure-track and professional practice positions are expected to effectively teach undergraduate and graduate courses, actively participate in assigned department and university duties, and serve their professional society. Ideal candidates will have an interest in developing new courses and degree programs in AI/ML and its applications to engineering.

Qualifications

Minimum Qualifications – Tenure Track Appointment

An earned doctorate degree in Electrical Engineering, Computer Engineering, Computer Science, Mathematics, Statistics, or a closely related discipline.

An ability to conduct and disseminate research that applies AI/ML to problems in the electrical engineering domain.

An ability to develop courses in AI/ML and effectively teach undergraduate and graduate level courses in AI/ML and the candidate’s specific area of research emphasis in accordance with departmental needs.

An ability to apply for and secure ongoing external funding.

Preferred Qualifications – Tenure Track Appointment

Preference will be given to candidates with experience building and deploying AI/ML systems.

 

Minimum Qualifications – Professional Practice Appointment

An earned MS degree in Electrical Engineering, Computer Engineering, Computer Science, Mathematics, Statistics, or equivalent work experience.

Strong industrial, commercial, consulting, or research experience in AI/ML systems.

An ability to develop courses in AI/ML and effectively teach undergraduate and graduate level courses in AI/ML and the candidate’s specific area of research emphasis in accordance with departmental needs.

Effective written and oral communication skills.

Demonstrated strong organizational skills.

Preferred Qualifications – Professional Practice Appointment

Effective teaching or mentoring experience.

Advanced degree in Electrical Engineering, Computer Engineering, Computer Science, Mathematics, Statistics or a closely related discipline.

Required Documents

Along with the online application, please attach:

Resume/CV to be uploaded at the beginning of your application in the Candidate Profile under “Resume/CV".

The documents listed below to be uploaded at the beginning of your application in the Candidate Profile under “Documents 1-10”:

Cover letter summarizing your motivation, qualifications, experience, and career goals.

A concise statement of your proposed research program including how your research synthesizes AI/ML and engineering topics.

A brief teaching statement that explains your approach to teaching and describes AI/ML courses you would like to develop and existing ECE courses you would like to teach.

Names and contact information of three professional references (reference letters will only be solicited from final candidates).

**Document size may not exceed 10 MB.**

Advertised Salary

Commensurate with experience, plus excellent benefits

ADA

Employees typically work indoors and are protected from weather and/or contaminants, but not, necessarily, occasional temperature changes.  

College/Department Highlights

The Department of Electrical and Computer Engineering (http://ece.usu.edu) offers BS, ME, MS, and PhD degrees. It has approximately 20 tenured/tenure