Research Assistant Professor​/Junior Research Economist

Position: Research Assistant Professor/ Junior Research Economist
Description & Details:

Junior Research Economist at the Rank of Research Assistant Professor

The Department of Agribusiness and Applied Economics at North Dakota State University seeks to appoint a promising early-career research economist to conduct grant-funded research on food retail market boundaries, competition, and consumer shopping behavior. The position is funded by the National Institute of Food and Agriculture and is a full-time, non-tenure track appointment. The initial appointment at the rank of Research Assistant Professor will be for two years with the possibility of extension based on performance and continued availability of grant funding.

The successful candidate will join a collaborative research team led by Dr. Sandro Steinbach at North Dakota State University in partnership with Dr. Cristina Connolly at the University of Connecticut. The project will advance knowledge on how food retail markets are defined, how competition operates across space and time, and how market structure measures change when markets are defined using business establishment information versus revealed consumer visitation patterns.

The research will combine empirical methods from industrial organization, spatial economics, and applied econometrics with scalable data engineering and interpretable machine learning.

This position provides an outstanding opportunity for independent research and opportunities for collaboration. The research assistant professor is expected to participate in the University's intellectual life actively and to contribute to peer-reviewed publications, conference presentations, and other research products emerging from the project. Work will emphasize reproducible research practices, transparent documentation, and the development of practical tools that enable researchers and analysts to replicate market boundary estimation and competition measurement.

Primary Responsibilities

Conduct independent and collaborative research on the boundaries of the food retail market and the competition dynamics at the establishment level.

Support the construction and harmonization of large-scale datasets that link food retail establishments to neighborhood characteristics and consumer visitation patterns.

Implement and estimate spatially aggregated discrete-choice demand models to delineate store-level market boundaries.

Develop and apply interpretable machine learning methods to identify key drivers of consumer store choice, validate model performance, and conduct sensitivity and out-of-sample checks.

Compare market boundaries inferred from structural demand modeling with boundaries implied by observed consumer flows, and document areas of agreement and systematic divergence.

Produce research manuscripts and technical documentation suitable for peer-reviewed outlets and stakeholder-oriented audiences, and present findings at academic and professional conferences.

Contribute to project dissemination activities, including preparation of supporting materials for a project website, code repositories, and user-oriented implementation guidance.

Provide mentorship and research training support to graduate and advanced undergraduate students as appropriate, including practicum-style work in data processing, spatial analysis, and applied econometrics and machine learning.

Work Schedule:

Full-time, non-tenure track appointment

Hiring Range:

$57,500-$62,500

Pay is based on several factors, including budget, labor market, prior experience, skills, knowledge, abilities, education, licensure and/or certification and other business considerations.

Minimum Qualifications:

Successful applicants must have received a doctoral degree in agricultural economics, applied economics, economics, or a closely related field, preferably within the last two to three years (or expected before the start date). Equivalent foreign degrees are acceptable.

Applicants must demonstrate excellent oral and written communication skills and strong quantitative training.

Applicants should have experience with applied microeconometrics and empirical industrial organization and demonstrated proficiency working with large datasets.

Strong coding skills in…