Assistant Professor of Computer Engineering and Computer Science

• Ph.D. in Computer Science, Computer Engineering, or a related computing or engineering field, including but not limited to Electrical Engineering, Electrical and Computer Engineering, Information Science, Data Science, or Quantum Information Science. Degree at time of application or official notification of completion of the doctoral degree by August 1, 2027.
• Demonstrated potential for effective teaching at the undergraduate and/or graduate levels in computer science, computer engineering, or related computing disciplines
• Demonstrated potential for scholarly research in computer science, computer engineering, or related computing disciplines
• Demonstrated commitment to working successfully with a diverse student population, including low socioeconomic and first-generation students

• Demonstrated scholarly productivity, as evidenced by published, peer-reviewed journal articles and conference papers in computer science, computer engineering, or related disciplines, with greater emphasis on research contributions within the past five years
• Demonstrated expertise or research experience in one or more emerging areas of computer engineering and computer science, including but not limited to quantum computing, quantum systems and engineering, AI accelerators, system-on-chip design, edge computing, cybersecurity and hardware security, data-intensive computing systems, and emerging computing paradigms. Additional areas of interest include high-performance computing, advanced distributed computing, cyber-physical systems, advanced computer architectures, and hardware–software co-design, particularly those advancing next-generation computing systems
• Demonstrated academic preparation, teaching experience, or professional expertise supporting the ability to teach multiple existing undergraduate and/or graduate courses in the Department of Computer Engineering and Computer Science
• Documented college-level teaching experience, including serving as an instructor of record, teaching assistant, or in a comparable instructional role
• At least one year of relevant postdoctoral or high-tech industry experience beyond degree-program responsibilities
• Experience successfully working with populations demographically and/or socioeconomically similar to the CSULB student body
• Experience mentoring or supporting students using inclusive and culturally relevant teaching strategies in a diverse classroom

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• Teach undergraduate and graduate courses in computer engineering, computer science, and related computing disciplines, including existing departmental courses. (Mode of instruction is primarily in-person, with the possibility of hybrid, online, or blended formats.)
• Contribute to the development, assessment, and continuous improvement of undergraduate and graduate curricula, including the integration of emerging technologies and the development of new courses in advanced areas of computer engineering and computer science
• Establish and maintain an active research program that contributes to advancements in computer engineering, computer science, or related disciplines, resulting in peer-reviewed scholarly publications, with efforts to secure external research funding
• Advise and mentor undergraduate and graduate students, including involving students in research and scholarly activities, to support their academic and professional development
• Provide service to the department, college, university, and broader academic and professional communities
• Work collaboratively and professionally with faculty, staff, and students in teaching, research, curriculum development, and departmental activities, fostering an environment of mutual respect, constructive communication, and shared academic responsibility

CSULB seeks to recruit faculty who enthusiastically support the University’s strong commitment to the academic success of all of our students, including students with disabilities, students who are first generation to college, veterans, students with diverse socio-economic backgrounds, and students of diverse sexual orientations and gender expressions. CSULB seeks to recruit and retain a diverse workforce as a reflection of our commitment to serve the People of California, to maintain the excellence of the University, and to offer our students a rich variety of expertise, perspectives, and ways of knowing and learning.

Information on excellent benefits package available to CSULB faculty is located here: CSU Employee Benefits

• A Student Success Statement about your teaching or other experiences, successes, and challenges in working with a diverse student population (maximum two pages, single-spaced). For further information and guidelines, please visit: Student Success Statement
• Letter of application addressing the required and preferred qualifications
• A current CV that clearly identifies published, peer-reviewed journal articles and conference papers, including publication dates and DOI or publication links, where available
• Names and contact information for three references (to be contacted for confidential letters of recommendation should you reach the semi-finalist stage)
• Teaching Statement (maximum three pages): A statement describing your teaching philosophy, instructional approaches, and relevant teaching and mentoring experience. Please identify existing CECS undergraduate and/or graduate courses you are prepared to teach, referencing specific course numbers and briefly explaining how your academic preparation, teaching experience, research expertise, or professional background supports your ability to teach these courses
• Research Statement (maximum three pages): A statement describing your past research accomplishments, current research activities, and future research agenda, with particular emphasis on scholarly contributions within the past five years and proposed research directions relevant to computer engineering and computer science
• Evidence of Teaching Effectiveness (if available): Supporting documentation such as student evaluations, peer teaching observations, or other relevant assessments of instructional effectiveness. This documentation is optional
• Finalists should be prepared to submit an official transcript (e-transcript preferred, if available)