Assistant​/Associate​/Professor in AI Image Analysis and Computer Vision

Position: Assistant/Associate/Professor in AI for Image Analysis and Computer Vision
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Posting Details

The University of Utah, an AA/EO employer, encourages applications from all qualified individuals, and provides reasonable accommodation to the known disabilities of applicants and employees. The University of Utah values candidates who have experience working in settings with students, staff, faculty and patients from all backgrounds and possess a strong commitment to improving access to higher education, employment opportunities, and quality healthcare for historically underrepresented groups.

Position Information

Proposed Faculty Rank Assistant/Associate/Professor Department 00062 - School of Computing City Salt Lake City, UT Track Tenure Track New Position to Begin January 1, 2026 Details

Kahlert School of Computing and Scientific Computing & Imaging Institute

University of Utah

The Kahlert School of Computing of the Price College of Engineering (Kahlert School) and the Scientific Computing and Imaging Institute (SCI) at the University of Utah seek applications for an open-rank (Assistant, Associate, or Full Professor) tenure-track or tenured faculty position in the broad area of Artificial Intelligence (AI) with a focus on Image Analysis and Computer Vision.

Position Overview

This position is part of a strategic expansion in artificial intelligence (AI), image analysis, and data science at the Kahlert School and the SCI Institute at the University of Utah. Both the Kahlert School and the SCI Institute are expanding their research strengths, with multiple new faculty hires at the intersection of computational science, data science, and science and engineering broadly.

These hires will enhance the SCI Institute's internationally recognized expertise in scientific, information, and biomedical visualization; image and data analysis; and interdisciplinary scientific computing and computational science. Kahlert School is a highly collaborative and collegial community that values and supports faculty engaged in cross-area and interdisciplinary research, providing a dynamic environment for AI-driven discovery.

The successful candidate will have the opportunity to lead collaborative AI-driven research that spans foundational and applied computing, leveraging the strengths of Kahlert School and the SCI Institute. Their work will bridge core computing disciplines-such as computer vision, large-scale AI systems, and machine learning-with cutting-edge, high-impact applications in scientific discovery, biomedical computing, computational medicine, and data-driven modeling. A major goal of this strategic expansion is to foster interdisciplinary partnerships across the University and with external collaborators, advancing AI-driven breakthroughs that transform computing, real-world imaging applications, and scientific and biomedical discovery.

What We Seek

We seek an accomplished and visionary researcher at the forefront of artificial intelligence (AI)-driven image analysis, computer vision, and computational imaging. The ideal candidate will have a strong track record of developing foundational AI methodologies and translating them into innovative applications in image-centric data analysis, AI-driven computational discovery, and interdisciplinary problem-solving across scientific and biomedical domains. Successful candidates are expected to have an established research program, a history of extramural funding, and a strong publication record in high-impact venues, demonstrating their leadership in AI-driven imaging research.

Their work should contribute to novel AI-driven approaches for extracting, interpreting, reconstructing, and enhancing visual information, fostering interdisciplinary collaborations and expanding the impact of AI in scientific computing and real-world problem-solving.

We are looking for candidates conducting high-impact, innovative research at the intersection of AI and imaging sciences. Areas of interest include, but are not limited to, foundational and applied advances in machine learning for image analysis, multimodal AI integrating imaging with other data modalities, physics-aware and hybrid modeling for imaging applications, scalable AI for high-dimensional visual data, trustworthy AI for image-based decision-making, and generative models for image understanding, reconstruction, and synthesis.

How to Apply

A PhD in computer science or a related field is required. Candidates are requested to submit (1) a curriculum vitae, (2) a cover letter (1-2 pages) describing their professional experience, including scientific accomplishments and leadership responsibilities, (3) a research statement (3-4 pages), (4) a teaching statement (1-2 pages), and (5) three references.

In their research statement, candidates should describe their vision for AI-driven image-centric computational research, including both foundational and applied aspects, and how their work aligns with and enhances the strengths of both the Kahlert School and the SCI…