Assistant Professor of AI & ML: Foundations & Teaching

The University of Kansas; Lawrence (KS); On-site; USD 110,000 - 140,000; Full time

Job summary

The University of Kansas (KU) invites applications for a full-time, tenure-track Assistant Professor position in Computer Science with a focus on artificial intelligence and machine learning. Candidates will contribute to teaching, develop an externally funded research program, and engage in service within KU’s EECS department and affiliated centers.

Topics include ML/deep learning, NLP, vision, multimodal learning, reinforcement learning, agentic AI, and secure AI systems, with collaboration

Qualifications

• Earned doctorate in computer science or a closely related field by the time of appointment.
• Demonstrated potential for teaching undergraduate and graduate courses at the university level.
• Expertise in the broad area of artificial intelligence and machine learning, including deep learning, generative AI and foundation models, NLP, computer vision, multimodal learning, RL and agentic AI, trustworthy and secure AI, and scalable AI systems.

Responsibilities

• Teach undergraduate and graduate courses in the EECS department and advise students.
• Establish and lead a strong research program with external grant potential and publications.
• Perform department, school, university, and professional service duties appropriate to the discipline.

Skills

Artificial intelligence

Machine learning

Deep learning

NLP

Computer vision

Multimodal learning

Reinforcement learning

Agentic AI

Trustworthy AI

Secure AI

Scalable AI systems

Human-AI interaction

Education

Doctorate in Computer Science

Job description

The University of Kansas (KU) invites applications for a full-time, tenure-track Assistant Professor position in Computer Science with a focus on artificial intelligence and machine learning. Candidates will contribute to teaching, develop an externally funded research program, and engage in service within KU’s EECS department and affiliated centers.

Topics include ML/deep learning, NLP, vision, multimodal learning, reinforcement learning, agentic AI, and secure AI systems, with collaboration