Assistant​/Associate Professor of Artificial Intelligence and Machine Learning in Veterinary Pop

Job Title:

Assistant/Associate Professor of Artificial Intelligence and Machine Learning in Veterinary Population Health Department:
Veterinary Medicine | Veterinary Preventive Medicine

Tenure faculty (regardless of rank) - persons with the titles of professor, associate professor, assistant professor and instructor who serve on appointments totaling 50% or more service to the university and who are eligible for tenure or who have obtained tenure. Duties and responsibilities are assigned in accordance with the workload guidelines laid out in the pattern of administration of each faculty member’s tenure initiation unit (TIU) and, as appropriate, regional campus;

obligations will include research, service and/or teaching or clinical practice. These faculty will have earned doctorate or other terminal degree in the relevant field of study or possession of equivalent experience.

Assistant/Associate Professor of Artificial Intelligence and Machine Learning in Veterinary Population Health

The Department of Veterinary Preventive Medicine in the College of Veterinary Medicine at The Ohio State University invites applications for a full-time, tenure-track faculty appointment at the rank of Assistant or Associate Professor, specializing in Artificial Intelligence (AI) and Machine Learning (ML). We seek an AI/ML scholar whose research focuses on developing and applying innovative computational methods to address critical challenges in veterinary medicine, disease prevention and control, and population health.

Ideal candidates will have a strong background in AI/ML and a demonstrated ability to translate advanced analytical approaches into meaningful discoveries and practical applications relevant to animal health and welfare. This position complements The Ohio State University’s AI Hiring Initiative to harness AI to revolutionize the translation of ideas to real-world solutions for Ohio and beyond.

The primary responsibilities of this position will be to conduct innovative, translational research at the intersection of advanced computational data science and veterinary medicine. Candidates must demonstrate significant AI/ML expertise as a core element of their scholarship through the development of novel methods or the application of existing approaches that generate new scientific knowledge, methodological advances, or practice solutions for veterinary preventive medicine and population health.

The successful candidates will maintain an extramurally funded research program that prioritizes translational science discoveries using novel approaches that support animal health and/or welfare. The position is intended for faculty whose scholarly contributions are centered on AI/ML and their advancement or innovative application in veterinary and population health contexts, rather than the routine use of existing AI tools.

In addition to research, the successful candidate is expected to maintain a teaching program. Teaching responsibilities will include providing instruction to veterinary and graduate students on topics that may include preventive medicine, animal welfare, and/or disease diagnosis and prevention and control. The candidate may also be expected to develop and deliver content that expands AI literacy and promotes the responsible and effective use of AI tools in veterinary medicine and related disciplines.

The successful candidate is expected to serve in department, college, and university level initiatives including the OSU AI(x) Hub

that aims to pioneer AI innovation for the public good. They will also have the opportunity to engage with regulatory agencies and external stakeholders to use AI to advance veterinary medicine. The specific distribution of effort will be adjusted to reflect the strengths and interests of the successful candidate but will remain predominately focused on research.

• Conduct translational research using AI/ML approaches to address challenges in veterinary medicine, disease prevention and control, and population health. Illustrative examples include:

• Traditional and syndromic disease surveillance

• Precision livestock farming, herd health informatics, and integrated decision support

• Predictive modeling for disease prevention, diagnosis, treatment, and population health and welfare management

• Population genomics, genetics and epidemiological forecasting

• Develop and maintain a nationally and internationally recognized, extramurally funded research program focused on applied AI and machine learning in preventive veterinary medicine and population health.

• Collaborate across disciplines (e.g., computer science, data analytics, public health, agriculture, medicine, and veterinary medicine) to foster cross-cutting research.

• Deliver high-quality instruction in core and elective topics, which may include veterinary preventive medicine, epidemiology, animal welfare, and…