The Artificial Intelligence (AI) Institute (http://ai.sc.edu) is a new university-wide institute engaged in core AI research, as well as high-impact interdisciplinary research involving AI implementations and applications. It is an outcome of the university’s Presidential Excellence Initiative, which seeks to bring national prominence to our college and university through AI research and its economic impact. This institute is the newest strategic focus area for the College and comes on the heel of other strategic hiring initiatives that have resulted in the addition of 30 new tenured or tenure track faculty since August 2017. We seek multiple tenured and tenure-track faculty members at all ranks and in all core-AI subareas, including scholars in interdisciplinary fields at the intersection of AI with computational engineering disciplines.
- For core-AI: Applicant is required to possess a Ph.D. degree in computer science or a closely related field by the beginning date of employment and have a demonstrated superior record of research accomplishments.
- For interdisciplinary AI: Applicant is required to possess a Ph.D. degree in one of the areas/departments covered by the College by the beginning date of employment and have a demonstrated expertise and impact in AI implementations and applications.
- The successful applicant is expected to develop internationally-recognized, externally-funded research programs that: (1) broaden the institution’s strengths, (2) leverage exceptional interdisciplinary collaboration opportunities (the AI Institute has collaborations with other UofSC colleges, including public health, medicine, pharmacy, nursing, information and communication, education, and arts and science, and (3) align with vital college-level, cross-cutting research themes, including smart & connected communities, transformative computing, healthcare transformations, and agile manufacturing (for example, see http://bit.ly/AIInst).
- The successful applicant is expected to demonstrate evidence of commitment to diversity, equity, and inclusion through research, teaching, and/or service efforts.
- Human in the loop or knowledge-enhanced AI, deep learning, natural language processing, question-answering/conversational AI, brain-inspired computing, semantic/cognitive/perceptual computing;
- AI and Big data - including social, sensor, biological, and health - and scalable computing/analysis of big data;
- AI and computer vision, robotics, cyber-physical systems, human-computer interaction including personal digital/assistive technology, autonomous vehicles, etc.