Artificial Intelligence | Genomics | Biotechnology | Precision Animal Systems
Develop the next generation of data analytics and AI-enabled methods for selecting animals, deriving novel phenotypes, and implementing precision management or interventions to improve animal production systems.
Position
Purdue University invites applications for a tenure-track assistant professor position focused on data analytics and artificial intelligence (AI)-enabled selection in animal systems. This position will be housed in Indianapolis where the candidate will have the opportunity to shape the academic and research programs offered there. We seek an innovative scholar who develops and applies AI, machine learning, data science, genomics, biotechnology, and predictive modeling to improve decision-making across animal agriculture. The successful candidate will use advanced data science and AI-enabled techniques in areas of interest, including selection and breeding of animals, derivation of novel traits and high-throughput phenotypes, health interventions, infectious disease control, precision management strategies, or production systems. The ultimate goal is to help create the next generation of intelligent animal agriculture. Candidates developing foundational or applied methods in AI, computational biology, quantitative genetics, engineering, bioinformatics, multi-omics data analytics, statistics, or related fields whose work can accelerate improvement across livestock, poultry, aquaculture, companion animals, biomedical animal models, and other relevant animal systems are encouraged to apply. Prior research centered on agricultural animals is valued but not required when a candidate's expertise can be applied to consequential problems in animal agriculture and health.
The successful candidate will establish an internationally recognized and externally funded research program; collaborate across disciplines; mentor graduate students and postdoctoral scholars; and contribute to undergraduate and graduate education. The anticipated appointment will be in the Department of Animal Sciences with opportunities for collaboration and appropriate joint or courtesy appointments across Purdue.
Grand Challenge
How can advanced data analytics and AI enable faster, more accurate, and responsible genetic improvement and precision management to enhance animal health, resilience, productivity, welfare, and sustainability?
Potential Areas of Scholarship
- AI-enabled selection, breeding, and genetic improvement, including genomic prediction of breeding values and phenotypes and next-generation quantitative genetics
- Machine learning and foundation models that integrate genomic, phenotypic, environmental, management, imaging, sensor, and multi-omics data
- High-throughput and digital phenotyping using computer vision, acoustic monitoring, wearable and spectroscopic technologies, robotics, and advanced sensing/diagnostics
- Selection of animals and derivation of novel traits for animal health and welfare, disease resistance, climate resilience, reproduction, efficiency, and product quality
- AI-guided selection of nutritional, microbiome, therapeutic, or management interventions
- Digital twins, causal models, and decision systems that predict animal performance across environments and production systems
- Responsible and transparent AI, including model validation, interpretability, uncertainty, fairness, data governance, and deployment in real-world animal systems
- Large-scale and complex data integration from diverse livestock data sources
- Precision animal agriculture, autonomous monitoring, and producer-facing decision support
- One Health applications connecting animal, human, food, and environmental health
Responsibilities
- Develop a high-impact, externally funded research program in AI-enabled selection for farm animal systems.
- Publish foundational and translational scholarship in impactful venues in the field and develop data resources, algorithms, software, intellectual property, computing infrastructure, or deployable technologies as appropriate.
- Build interdisciplinary collaborations across agriculture, engineering, computing, veterinary medicine, life sciences, statistics, health, and livestock industries.
- Teach courses aligned with the candidate's expertise and contribute to curricula in AI, data science, genomics, biotechnology, quantitative methods, or animal systems. Course modality is in person. The potential may exist for teaching online/distance courses during the academic year.
- Mentor undergraduate students, graduate students, visiting scholars, and postdoctoral researchers.
- Contribute service and engagement consistent with Purdue's land-grant mission.
