About this role
Job Summary
The Purdue University College of Agriculture seeks applicants for a tenure-track Assistant Professor of Computational Agricultural and Natural Systems Modeling. This is a full-time (9-month) position with an appointment in research and teaching. The successful candidate will be appointed in an appropriate academic department within the College of Agriculture, based on their disciplinary expertise and research program. The position is intended for a scholar who can develop and lead a rigorous computational research program to improve the performance and resilience of agricultural, food, biological, environmental, and natural-resource systems.
We seek candidates whose research advances the understanding, prediction, design, or management of complex systems through mechanistic, statistical, data-driven, or hybrid modeling approaches and advanced computational methods. The successful candidate should be able to develop new models, computational methods, data integration pipelines, and decision-support frameworks for agricultural and related systems. The candidate's program should draw on quantitative methods such as modeling, optimization, decision science, artificial intelligence (AI), machine learning, bioinformatics, or related computational approaches.
Within the context of agricultural, biological, environmental, food, and natural-resource systems, we are looking for candidates with experience in one or more of the following areas: Modeling and predictive science Mechanistic, statistical, and hybrid modeling Machine learning and AI Mathematical and computational biology Complex systems, network science, and uncertainty quantification Systems design and decision science Optimization and operations research Decision analysis and risk assessment Digital twins as a decision/optimization framework Scenario analysis and robust decision-making Computational integration and scale Geospatial and spatiotemporal analytics for systems-level decision-making/resource allocation High-performance, cloud computing, and computational/software infrastructure Integration of diverse and large-scale datasets from precision farms Reproducible computational workflows Interoperable models, data, and software architecture Applications of the work could relate to agricultural production and natural systems, plant or animal breeding and genetics, soil health, animal agriculture, insect and disease systems, water resources, forestry, microbiomes, food systems, conservation planning, supply chains, logistics, transportation systems, rural and agricultural communities, agricultural policy, and regional or global food systems.
We expect the candidate to build a nationally and internationally recognized research program that advances discovery and delivers robust, decision-ready modeling and computational tools for agricultural, environmental and natural-resource systems. The successful candidate will teach graduate and/or undergraduate courses in areas such as systems modeling, computational science, scientific machine learning, decision analysis, optimization, reproducible computation, or data-model integration.
Course modality is generally in person. The potential may exist for teaching online/distance courses during the academic year. The candidate will also mentor students from disciplinary backgrounds who need advanced computational preparation to address agricultural and life-science problems.
The College The College of Agriculture is one of the world's leading colleges of agricultural, food, life, and natural-resource sciences. The College is ranked third in the United States and sixth in the world in the 2026 QS World University Rankings. The College is deeply committed to the three land-grant missions of teaching, research, and Extension, to international activities and perspectives that span all missions, and to excellence in all we do. The College has 10 academic departments, 294 faculty, 2,842 undergraduate students, and 694 graduate students.
The successful candidate will have opportunities to collaborate with faculty affiliated with interdisciplinary initiatives and centers including the Institute for Digital and Advanced Agricultural Systems, Institute for Plant Sciences, Center for Plant Biology, Institute for Digital Forestry, Institute for a Sustainable Future, Indiana Water Resources Research Center, Institute for Physical Artificial Intelligence (IPAI), Purdue Computes, Purdue's One Health Initiative, and a growing ecosystem of AI, computing, sustainability, and resilient systems programs.
Qualifications
Applicants must possess a Ph.D. degree by the start of appointment in agriculture, animal sciences, forestry and natural resources, biology, bioinformatics, ecology, environmental science, food science, engineering, computer science, data science, robotics, statistics, economics, applied mathematics, operations research, systems science, geography, computational science, quantitative social science, or a related discipline. A record of research excellence and productivity commensurate with rank is required, as well as demonstrated potential for interdisciplinary collaboration and impactful scholarship.
Optimization, decision science, bioinformatics, quantitative data and statistical methods, systems modeling, and/or computational science should represent a primary thread of the candidate’s research program. Candidates must demonstrate commitment to teaching and student mentorship and show potential to establish an externally funded research program that addresses important agricultural, environmental, biological, food, or natural-resource challenges.
Applicants will be evaluated on the significance and originality of their computational scholarship, the strength of their connection to one or more College mission areas, and their potential for collaboration, teaching, mentorship, and external funding—not on coverage of every method or application listed above. Ideal qualifications include experience integrating models, data, software, or computational workflows across disciplines or scales; expertise in biological, agricultural, environmental, economic, social, or engineered systems; and experience working in interdisciplinary teams. Experience with high-performance or cloud computing, optimization methods, and/or decision-analytic frameworks will be also highly valued.
Application Process Interested applicants must submit a cover letter indicating the top two preferred department homes in the College of Agriculture (click https://ag.purdue.edu, then departments), curriculum vitae, research statement, teaching statement, and contact information for at least three references. Review of applications will begin on November 30, 2026 and continue until the position is filled. Applications should be submitted at https://careers.purdue.edu/job/Assistant-Professor-of-Computational-Agricultural-and-Natural-Systems-Modeling/44631-en_US/ . Application materials must be combined into a single PDF and submitted electronically in the CV field on the application site. Contact Matt Ginzel ( [email protected] ) if you have questions. A background check is required for employment in this position. Purdue University Purdue University is an equal opportunity/equal access university.