Part-time Faculty, PhD Computer Science

National University•Remote, California, CA

2d•$27 - $29•Remote

About The Position

National University is seeking part-time faculty with a specialization in Computer Science for the Department of Engineering, Data and Computer Sciences. The successful candidate will have a demonstrated record of or potential for excellence in teaching in their field and a commitment to serving the university’s diverse adult student body. This position primarily works closely with the Academic Program Director and other faculty within the program and contributes to ensuring program quality, student engagement, and success.

Requirements

Ph.D. in the field of computer science or computer engineering from a regionally accredited university required.
A strong background in any of the following areas required: Advanced Artificial Intelligence and Machine Learning (e.g., deep learning, reinforcement learning, natural language processing, large-scale AI systems)
Data Systems and Data Engineering (e.g., database systems, distributed data systems, large-scale data processing, data-intensive applications)
Systems and Distributed Computing (e.g., operating systems, distributed systems, parallel computing, cloud and scalable systems)
Networking and Networked Systems (e.g., computer networks, distributed networking, modern communication systems)
Software Engineering and Programming Systems (e.g., programming languages, systems programming, software design and architecture)
Emerging areas aligned with computer science research (e.g., IoT systems, scalable platforms, trustworthy AI, quantum computing)

Nice To Haves

3+ years of higher education teaching experience preferred.
Experience teaching at the doctoral level, contributing to course development, and serving on dissertation committees preferred.

Responsibilities

Provide substantive, timely feedback to students on various assessment activities.
Maintain a positive, safe, inclusive student-centric learning environment.
Complete required tasks on deadlines (e.g., final grades, assessment, grading rubrics, input for grade appeals, etc.)
Maintain appropriate professional training and/or scholarly activities, when applicable.
Provide feedback to the course lead regarding the course content.
Identify at-risk students and collaborate with student services.