Three Faculty Positions in Data Science: Human-Computer Teaming and Interactive Decision Making; Artificial Intelligence Architectures; and Trustable
Positions Available:
Artificial Intelligence at the University of Oklahoma, Norman Campus
As part of a multiyear effort to grow world-class data science and data-enabled research across The University of Oklahoma (OU), the Gallogly College of Engineering (GCoE), Department of Electrical and Computer Engineering and/or Department of Computer Science, in partnership with the Dodge Family College of Arts and Sciences (CAS), welcomes applications for a cluster of three (3) faculty positions from candidates whose experiences and interests have prepared them to be an integral contributor engaged in scientific discovery, developing talent, solving global challenges, and serving our society. This year we are focusing on data science foundational and enabling technologies. In subsequent years, we'll be hiring additional data science and data-enabled research faculty.
The University, as part of its Lead On, University strategic plan has committed to creating world- class capabilities in data science, artificial intelligence (AI), machine learning (ML), and data-enabled research. In July 2020, the University established the Data Institute for Societal Challenges (DISC) to grow convergent data-enabled research to solve global challenges. DISC currently has over 130 faculty members across OU campuses, nine communities of practice, seed funding programs, and an extended network of approximately 300 data scientists and data- enabled researchers across many disciplines (https://www.ou.edu/disc).
Three positions:
1. Professor or Associate Professor in Human-Computer Teaming and Interactive Decision Making: Humans and computers have complementary knowledge and skill sets. To solve challenging problems, we need to team this expertise together for effectiveness, reliability, efficiency, and adoption of many data-driven solutions. This area is cross-disciplinary, and we seek a senior faculty member with expertise in one or more of human-computer teaming, visualization, visual analytics, human-machine interaction, decision theory, HCI, human factors and industrial engineering, or cognitive psychology. This faculty member will be a vital core team member in data science and data-driven decision making with a home department in ECE and possible joint appointments in ISE, Computer Science, Psychology, and/or Political Science.
Applications should be submitted online via Interfolio at https://apply.interfolio.com/112374
Inquiries can be addressed to Professor David Ebert, chair of the search committee at ebert@ou.edu.
2. Assistant Professor in AI Architectures: We seek to recruit a transdisciplinary faculty member with expertise in one or more of the following areas: scalable, high-performance software and hardware architectures for AI and advanced analytics, advanced and domain-tailored data science, AI (trustable, science-based, and human-guided), and human-computer teaming. Specific areas of interest include probabilistic, neuromorphic, and novel architectures, software pipelines and operating system architectures to support high-performance analytics, and enable real-time trustable AI and decision-making. Since traditional computing architectures are still based on solving problems from the 20th century, new computing hardware and software architectures are needed to optimize computing for AI and machine learning and many new approaches to science and engineering. This faculty member will grow and complement work in computer engineering, computer science and the new OU quantum center (CQRT) with a home department in ECE and possible joint appointments where appropriate.
Applications should be submitted online via Interfolio at https://apply.interfolio.com/112359
Inquiries can be addressed to Professor David Ebert, chair of the search committee at ebert@ou.edu
3. Assistant Professor in Trustable AI. http://apply.interfolio.com/112359. We are seeking an Assistant Professor in Trustable AI. Human-guided, science-based, explainable AI (xAI) are key areas to ensure AI is understandable, reliable, and robust for real-world applications. This faculty member will grow our expertise in one of the most rapidly developing and vital fields of data science, with a primary home in ECE and potentially joint appointments in CS, Psychology, and ISE. We seek a faculty member with expertise in one or more of science-based AI or machine learning (ML), human-guided AI/ML, explainable AI/ML, and closely related topics. This faculty member will be a vital core team member in data science, AI, and data-driven convergent research solutions to global challenges. This faculty member will provide vital capabilities that will empower research in all four strategic verticals and grow the data science ecosystem on campus to create the critical mass in data science needed for the success of the university's strategic plan, Lead On, University.
Applications should be submitted online via Interfolio at http://apply.interfolio.com/112372.
Inquiries can be addressed to Professor David Ebert, chair of the search committee at ebert@ou.edu.
For more information, please refer to the attached document.
Talayeh Razzaghi, Ph.D.
Assistant Professor
School of Industrial and Systems Engineering
Data Science and Analytics Institute
Gallogly College of Engineering
University of Oklahoma