The Ohio State University  

Columbus, OH

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. 

Performance Objectives 

• 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 data-driven disease prevention and control 

• Contribute to educational activities that expand AI literacy and promote the responsible use and evaluation of AI in veterinary medicine 

• Mentor graduate students (MS/PhD) and postdoctoral fellows in applied data science and population health 

• Engage with profession organizations, regulatory agencies, and industry stakeholders to advance the field of veterinary medicine 

• Provide service to the department, college, and university through committee participation, academic governance, and participation in OSU AI(X) Hub.  

Education and Experience Requirements 

Ideal candidates will demonstrate significant AI expertise as a core element of their scholarship whether through the creation of new AI methods or novel use of AI techniques that materially advance knowledge, methods, or practice in their discipline.  

For this search, “AI” includes (but is not limited to) Machine Learning (ML), Deep Learning, Reinforcement Learning, Optimization for/with ML, Probabilistic Modeling, Trustworthy/responsible AI (fairness, safety, privacy, robustness, interpretability), Human-centered AI, Natural Language Processing (NLP), Computer Vision, Robotics, Scientific/Physics-informed Machine Learning (ML), AI Systems and Infrastructure, Domain-driven AI advancements in and across disciplines.   

In addition to the disciplinary requirements for potential selection as a faculty, a qualified candidate will develop, advance, or rigorously evaluate AI methods, lead AI-centered applications that produce generalizable methodological advances (e.g., new algorithms, models, evaluation frameworks, datasets/benchmarks, or system designs), design/adapt AI approaches to solve previously intractable questions in a domain leading to generalizable insights advancements.    

Routine use of off-the-shelf AI tools that does not produce methodological innovation, or field-advancing knowledge is not sufficient for an AI faculty hire for this initiative.  

Required:  

• DVM (or equivalent) or a PhD in Epidemiology, Veterinary Preventive Medicine, Biomedical Informatics, Computer Science, Data Science, or a closely related field. 

• Demonstrates a track record of scholarship centered on AI/ML methodologies applied to biological, medical, or population-level data. 

• Evidence of, or strong potential for, securing extramural research funding. 

• Strong communication skills  

Desired:  

• Both a DVM and a PhD in an AI relevant field 

• Board certification (or eligibility) in a relevant veterinary specialty (e.g., ACVPM, ACZM, ACVM) 

• Hands-on experience deploying AI/ML models in practical, clinical, agricultural, or wildlife settings 

• Prior experience teaching epidemiology, biostatistics, or digital health concepts to non-computational learners 

Additional Information 

The offer for this position will be based on internal equity and the candidate's qualifications.  

Ohio State provides access to a depth and breadth of opportunities and resources. Starting your first day, Ohio State offers you a comprehensive benefits package. 

How to Apply 

To be considered, please submit your application electronically via Workday [insert link to posting for advertisements]. Application materials must include:  

Application closes 09/15/2026 

https://osu.wd1.myworkdayjobs.com/OSUCareers/job/Columbus-Campus/Assistant-Associate-Professor-of-Artificial-Intelligence-and-Machine-Learning-in-Veterinary-Population-Health_R157662-1

The university is an equal opportunity employer, including veterans and disability. 

The Ohio State University  

Columbus, OH

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. 

Performance Objectives 

• 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 data-driven disease prevention and control 

• Contribute to educational activities that expand AI literacy and promote the responsible use and evaluation of AI in veterinary medicine 

• Mentor graduate students (MS/PhD) and postdoctoral fellows in applied data science and population health 

• Engage with profession organizations, regulatory agencies, and industry stakeholders to advance the field of veterinary medicine 

• Provide service to the department, college, and university through committee participation, academic governance, and participation in OSU AI(X) Hub.  

Education and Experience Requirements 

Ideal candidates will demonstrate significant AI expertise as a core element of their scholarship whether through the creation of new AI methods or novel use of AI techniques that materially advance knowledge, methods, or practice in their discipline.  

For this search, “AI” includes (but is not limited to) Machine Learning (ML), Deep Learning, Reinforcement Learning, Optimization for/with ML, Probabilistic Modeling, Trustworthy/responsible AI (fairness, safety, privacy, robustness, interpretability), Human-centered AI, Natural Language Processing (NLP), Computer Vision, Robotics, Scientific/Physics-informed Machine Learning (ML), AI Systems and Infrastructure, Domain-driven AI advancements in and across disciplines.   

In addition to the disciplinary requirements for potential selection as a faculty, a qualified candidate will develop, advance, or rigorously evaluate AI methods, lead AI-centered applications that produce generalizable methodological advances (e.g., new algorithms, models, evaluation frameworks, datasets/benchmarks, or system designs), design/adapt AI approaches to solve previously intractable questions in a domain leading to generalizable insights advancements.    

Routine use of off-the-shelf AI tools that does not produce methodological innovation, or field-advancing knowledge is not sufficient for an AI faculty hire for this initiative.  

Required:  

• DVM (or equivalent) or a PhD in Epidemiology, Veterinary Preventive Medicine, Biomedical Informatics, Computer Science, Data Science, or a closely related field. 

• Demonstrates a track record of scholarship centered on AI/ML methodologies applied to biological, medical, or population-level data. 

• Evidence of, or strong potential for, securing extramural research funding. 

• Strong communication skills  

Desired:  

• Both a DVM and a PhD in an AI relevant field 

• Board certification (or eligibility) in a relevant veterinary specialty (e.g., ACVPM, ACZM, ACVM) 

• Hands-on experience deploying AI/ML models in practical, clinical, agricultural, or wildlife settings 

• Prior experience teaching epidemiology, biostatistics, or digital health concepts to non-computational learners 

Additional Information 

The offer for this position will be based on internal equity and the candidate's qualifications.  

Ohio State provides access to a depth and breadth of opportunities and resources. Starting your first day, Ohio State offers you a comprehensive benefits package. 

How to Apply 

To be considered, please submit your application electronically via Workday [insert link to posting for advertisements]. Application materials must include:  

Application closes 09/15/2026 

https://osu.wd1.myworkdayjobs.com/OSUCareers/job/Columbus-Campus/Assistant-Associate-Professor-of-Artificial-Intelligence-and-Machine-Learning-in-Veterinary-Population-Health_R157662-1

The university is an equal opportunity employer, including veterans and disability.