Instructor (I2) Applied Computing (PMCS) #0082794

Temporary/Permanent:

Permanent

Other Conditions:
Subject to position clearance and availability of funds. First review of applicants will begin January 15, 2026 with continuous recruitment until position is filled. 9-month renewal dependent upon performance and availability of funds.

Duties and Responsibilities:

• Help develop and implement the professional program courses.
• Teach one or more courses in the ICS Department’s Professional AI Program, including Applied Computing Industry Seminar, Applied Computing Fundamentals, Data Science and AI, and Practical Problem Solving with Algorithms.
• Oversee graduate teaching assistants and advising graduate students.
• Mentor students for capstone Internship projects.
• Network with industry and public sectors to identify projects.
• Network with industry and public-sector partners to identify and secure relevant project opportunities for students.

Minimum Qualifications:

• Master’s degree in Computer Science, Data Science or in a closely related field from a college or university of recognized standing.
• Ability to contribute to curriculum and course development in applied AI/Data Science.
• Strong written and oral communication skills.
• Ability to teach effectively and to direct group discussions.
• Prior teaching experience.
• Experience with modern AI frameworks such as PyTorch and the Hugging Face ecosystem, as well as familiarity with tools used in Generative AI workflows (e.g., LangChain, vector databases).

Desirable Qualifications:

• PhD in Computer Science or in a closely related field from a college or university of recognized standing.
• At least 2 years of professional experience in applied computing, AI or data science.
• Evidence of at least 5 years of professional experience in AI or Data Science.
• Strong commitment to professional graduate AI education.
• Experience teaching computer sciences courses for people without a computer science background.
• Experience in teaching in multiple modalities (online, face to face, hybrid, etc).