What are the responsibilities and job description for the Assistant or Associate Professor - Multimodal Artificial Intelligence (AI) and Natural Language Processing (NLP) position at University of Houston?
Department: Computer Science Salary: Commensurate with Experience/Education
Description
The Department of Computer Science at the University of Houston (www.cs.uh.edu) invites applications for a tenure-track faculty position at the Assistant or Associate Professor level. We are seeking candidates conducting innovative and impactful research in Multimodal Artificial Intelligence (AI) and Natural Language Processing (NLP).
We seek outstanding candidates with expertise in developing and applying AI techniques that integrate and reason over multiple modalities—including text, speech, vision, and sensor data—particularly in ways that advance natural language understanding, generation, and human-AI interaction.
Research topics of interest include, but are not limited to:
Large Language Models (LLMs) and multimodal foundation models
Cross-modal representation learning and alignment
Multimodal dialogue systems and conversational agents
Multimodal reasoning, summarization, and question answering
Low-resource, fair, and explainable multimodal NLP
Scalable and efficient training of multimodal systems
The Successful Candidate Will
Establish a vigorous, externally funded research program.
Collaborate with existing research strengths in AI, computer vision, human-computer interaction, and data science.
Contribute to curriculum development in AI, NLP, and multimodal computing.
Teach courses in the department of Computer Science.
Mentor graduate and undergraduate students.
Applicants must have a Ph.D. in Computer Science, Computer Engineering, or a closely related field by the start date of September 1, 2026, and should demonstrate an exceptional record of publications and strong potential for securing competitive research funding.
The Department of Computer Science is home to a dynamic and interdisciplinary group of 30 full-time faculty members and over 2000 students across its BS, MS, and PhD programs. The department currently has a strong emphasis on research in fundamental and applied computer science including AI, machine learning, computer vision, graphics and visualization, systems, distributed algorithms, and scientific and biomedical computing. Research in the department is and has been funded by numerous agencies, including the National Science Foundation, National Institutes of Health, National Institute of Standards and Technology, and the U.S. Departments of Defense, Homeland Security, Justice, Energy, and Transportation.
Located in Houston, the fourth largest city in the United States, UH is a Carnegie Tier One public research university that is located on a park-like campus a few minutes from the Houston city center. The university has embarked on an exciting period of research growth, a rising reputation, and committed leadership.
The city of Houston has world-class theaters, museums, restaurants, and thrilling sports teams. It offers affordable housing and enjoys a low cost of living. The university is close to the Texas Medical Center, the largest in the world, a large industrial base, and NASA.
Salary and rank will be commensurate with experience.
The university is responsive to the needs of dual-career couples.
Review of applications will begin immediately and continue until the position is filled. Prospective applicants are welcome to direct inquiries to Dr. Shishir Shah at sshah@central.uh.edu.
Official transcripts are required for a faculty appointment and will be requested upon selection of the final candidates.
All positions at the University of Houston-System are security sensitive and will require a criminal history check. Individuals conducting research in critical infrastructure areas (i.e., communication infrastructure systems, cybersecurity systems, electric grid, hazardous waste treatment systems, and/or water treatment facilities) are subject to regular review to ensure the security and integrity of the research is maintained.
The University of Houston System and its universities are Equal Opportunity Institutions. Everyone is encouraged to apply.
Description
The Department of Computer Science at the University of Houston (www.cs.uh.edu) invites applications for a tenure-track faculty position at the Assistant or Associate Professor level. We are seeking candidates conducting innovative and impactful research in Multimodal Artificial Intelligence (AI) and Natural Language Processing (NLP).
We seek outstanding candidates with expertise in developing and applying AI techniques that integrate and reason over multiple modalities—including text, speech, vision, and sensor data—particularly in ways that advance natural language understanding, generation, and human-AI interaction.
Research topics of interest include, but are not limited to:
Large Language Models (LLMs) and multimodal foundation models
Cross-modal representation learning and alignment
Multimodal dialogue systems and conversational agents
Multimodal reasoning, summarization, and question answering
Low-resource, fair, and explainable multimodal NLP
Scalable and efficient training of multimodal systems
The Successful Candidate Will
Establish a vigorous, externally funded research program.
Collaborate with existing research strengths in AI, computer vision, human-computer interaction, and data science.
Contribute to curriculum development in AI, NLP, and multimodal computing.
Teach courses in the department of Computer Science.
Mentor graduate and undergraduate students.
Applicants must have a Ph.D. in Computer Science, Computer Engineering, or a closely related field by the start date of September 1, 2026, and should demonstrate an exceptional record of publications and strong potential for securing competitive research funding.
The Department of Computer Science is home to a dynamic and interdisciplinary group of 30 full-time faculty members and over 2000 students across its BS, MS, and PhD programs. The department currently has a strong emphasis on research in fundamental and applied computer science including AI, machine learning, computer vision, graphics and visualization, systems, distributed algorithms, and scientific and biomedical computing. Research in the department is and has been funded by numerous agencies, including the National Science Foundation, National Institutes of Health, National Institute of Standards and Technology, and the U.S. Departments of Defense, Homeland Security, Justice, Energy, and Transportation.
Located in Houston, the fourth largest city in the United States, UH is a Carnegie Tier One public research university that is located on a park-like campus a few minutes from the Houston city center. The university has embarked on an exciting period of research growth, a rising reputation, and committed leadership.
The city of Houston has world-class theaters, museums, restaurants, and thrilling sports teams. It offers affordable housing and enjoys a low cost of living. The university is close to the Texas Medical Center, the largest in the world, a large industrial base, and NASA.
Salary and rank will be commensurate with experience.
The university is responsive to the needs of dual-career couples.
Review of applications will begin immediately and continue until the position is filled. Prospective applicants are welcome to direct inquiries to Dr. Shishir Shah at sshah@central.uh.edu.
Official transcripts are required for a faculty appointment and will be requested upon selection of the final candidates.
All positions at the University of Houston-System are security sensitive and will require a criminal history check. Individuals conducting research in critical infrastructure areas (i.e., communication infrastructure systems, cybersecurity systems, electric grid, hazardous waste treatment systems, and/or water treatment facilities) are subject to regular review to ensure the security and integrity of the research is maintained.
The University of Houston System and its universities are Equal Opportunity Institutions. Everyone is encouraged to apply.