Three Faculty Positions in Data Science
The University of Oklahoma – Norman Campus
Three Faculty Positions in Data Science: Human-Computer Teaming and Interactive Decision Making; Artificial Intelligence Architectures; and Trustable Artificial Intelligence
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) welcomes applications for a cluster of three (3) faculty positions.
1) Professor or Associate Professor in Human-Computer Teaming and Interactive Decision Making: Humans and computers have complementary knowledge and skillsets. 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 appoint in ISE, Computer Science, Psychology, and/or Political Science.
Applications should be submitted online via Interfolio at http://apply.interfolio.com/112374
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 http://apply.interfolio.com/112359
3) Assistant Professor in Trustable AI. 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
For inquiries contact:
Dr. David S. Ebert, Gallogly Chair Professor
School of Electrical and Computer Engineering and School of Computer Science
Associate Vice President of Research and Partnerships
Director, Data institute for Societal Challenges
University of Oklahoma
Email: [email protected]
Equal Employment Opportunity Statement
The University of Oklahoma, in compliance with all applicable federal and state laws and regulations does not discriminate on the basis of race, color, national origin, sex, sexual orientation, genetic information, gender identity, gender expression, age, religion, disability, political beliefs, or status as a veteran in any of its policies, practices, or procedures. This includes, but is not limited to: admissions, employment, financial aid, housing, services in educational programs or activities, or health care services that the University operates or provides.