ESE Lecturer 2026-2027

The Department of Electrical and Systems Engineering (ESE) within the School of Engineering and Applied Science (SEAS) at the University of Pennsylvania seeks outstanding applicants for a full-time lecturer position to teach courses in artificial intelligence, machine learning, and data science, with particular focus on applications of Artificial Intelligence (AI) and on computer systems and architectures for AI. The department seeks individuals with exceptional promise for, or a proven record of, excellence in undergraduate and graduate education. Appointments may be at Senior Lecturer or Lecturer rank commensurate with the candidate's experience and accomplishments. This position is non-tenure track. Candidates must have a commitment to excellence in undergraduate and graduate education in electrical and systems engineering or related areas, and a strong commitment to fostering a positive educational environment. The Department maintains close collaborations with all other engineering departments in SEAS and other Schools at Penn including the School of Arts and Sciences, the Perelman School of Medicine, the Wharton School of Business, and the Stuart Weitzman School of Design. The Department has strong interactions with leading centers including the General Robotics, Automation, Sensing, and Perception (GRASP) Laboratory, the Penn Institute for Computational Science (PICS), and the Penn Center for Health, Devices & Technology. Applicants should hold an advanced degree in an engineering discipline related to Artificial Intelligence including Electrical Engineering, Computer Engineering, Computer Science, Mechanical Engineering, Machine Learning, Data Science, or related areas. Applications must be submitted online via Interfolio (. Applicants must submit a CV, teaching statement, and contact information for three references for consideration. The University of Pennsylvania is an equal opportunity employer. Candidates are considered for employment without regard to race, color, sex, sexual orientation, religion, creed, national origin (including shared ancestry or ethnic characteristics), citizenship status, age, disability, veteran status or any class protected under applicable federal, state, or local law.