CIS Practice Assistant Professor 2027

The University of Pennsylvania’s Department of Computer and Information Science is pleased to welcome applications for experienced teaching faculty under the Practice Professor track. It is a very exciting time to be engaged in computer science education at Penn, as we are developing new curricular programming to embrace artificial intelligence’s increased role in the field. We are also developing multiple new on-campus and online learning programs.

We are seeking dedicated, accomplished, full-time faculty to teach undergraduate electives and Master’s-level courses, particularly in areas such as software engineering, artificial intelligence and data science, theoretical computer science, computer graphics, and cybersecurity, starting in July 2027. We seek individuals who promote and welcome wide-ranging viewpoints and experiences, and who will work closely with students of all backgrounds.

As part of teaching-track career path, the Practice Assistant Professor position seeks teaching-focused faculty members, who have a track strong record of research in engineering education and developing and publishing on innovative pedagogical techniques. Applicants who desire to pursue this track but do not yet have an extensive publication history are encouraged to apply also to our posting for a Lecturer or Senior Lecturer position

PhD in Computer Science or relevant discipline.

To ensure full consideration, applicants are encouraged to apply by November 15th, 2026. However, applications will be accepted until positions are filled. Please submit a cover letter, curriculum vitae, research statement, teaching statement, and names of 3 references. Other supporting documents are optional. Applications must be submitted online through (https://apply.interfolio.com/194863) Interfolio.

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.