Postdoctoral Researcher in Farm Labor Markets and Environmental Economics

Your role

We seek an innovative modeler focusing on the human social aspects of food systems transformation, specifically on labor markets. The successful candidate will investigate how European producers are adapting to intensifying labor scarcity, their exposure to heat stress and other changes to the food systems. The research will inform adaptations to structural changes in labor markets in the context of climate change.

The Postdoctoral researcher will utilise existing evidence and advanced fine-scale modelling techniques to deepen our understanding of the dynamics of farm labor markets. Ultimately, this work aims to strengthen sustainable food production systems and support the resilience of rural communities.

• Understand the drivers and impacts of intensifying farm labor scarcity on European food systems as well as spillovers to other regions
• Map the data landscape on farm workers in Europe by identifying key sub-groups of farm workers. Lead the development of a comprehensive and standardized fine-scale database that captures the diversity of farm worker typologies and labor market outcomes, including the identification and bridging of critical data gaps
• Acquire and apply state-of-the-art modelling techniques for fine-scale analysis of local agricultural systems, with integration to global market drivers influencing production decisions
• Support the development of Farm Labor module within multi-scale modelling framework for the agricultural sector, like the Simplified International Model for agricultural Prices, Land-use and the Environment, Gridded version – SIMPLE-G
• Use the module to evaluate how farm labor markets interact with expected changes in food systems, e.g., dietary preferences, climate change, e.g., labor heat stress, and policy initiatives
• Foster strong cross-disciplinary collaborations within LCSES, contribute to overlapping research themes where appropriate and further support the establishment of LCSES

For further questions regarding this position, please contact Dr. Srabashi RAY at srabashi.ray@uni.lu

Your profile

• A PhD in agricultural, environmental, or applied/environmental economics or a closely related discipline
• Experience with integrated assessment models and working with common coding languages
• Proven ability to independently conduct research and lead high-impact publications
• Proven expertise with fine-scale modelling and handling of large-scale datasets “big data”
• Previous work on policy evaluation related to biodiversity or agricultural sustainability
• Experience in GAMS or GEMPACK
• Proficiency in written and spoken English. Knowledge of Luxembourgish, French and/or German is an asset

We offer

• A modern, dynamic university with a personal and inclusive atmosphere. Multilingual and international character. Staff coming from more than 90 countries. Member of The Guild of European Research Intensive Universities
• An exceptional research environment, supported by skilled staff and high-quality equipment. Strong links to professional sectors and the Luxembourg labour market. A unique urban campus with excellent infrastructure
• A partner for society and industry. Cooperation with European institutions, innovative companies, the Financial Centre and a wide range of non-academic partners including ministries, local governments, associations, and NGOs

How to apply

Applications should include:

• Curriculum Vitae
• Cover letter detailing your motivation for applying to the advertised research topic and/or project, including how your background, interests, and career goals align with its objective
• PhD diploma
• Transcript of all modules and results from university-level courses taken
• List of publications
• Names, contact information and current position of 3 referees who can, upon request, provide an assessment of the application. Please indicate their relationship to you
• 2 papers in PDF (preferably published or in review)

Early application is highly encouraged, as the applications will be processed upon reception. Please apply ONLINE formally through the HR system. Applications by Email will not be considered.

All qualified individuals are encouraged to apply. In line with our values, the University of Luxembourg promotes an inclusive culture. We encourage applications from individuals of all backgrounds and are dedicated to upholding equality and respect for our employees and students.

General information:

• Contract Type: Fixed Term Contract 36 Month
• Work Hours: Full Time 40.0 Hours per Week
• Planned Start Date: 1 September 2026
• Location: Belval Campus
• Internal Title: Postdoctoral researcher
• Job Reference: UOL08211

The yearly gross salary for every Postdoctoral Researcher at the UL is EUR 85176 (full time).

About us

The University of Luxembourg is an international research university with a distinctly multilingual and interdisciplinary character.

The Luxembourg Centre for Socio-Environmental Systems strives to grow into an internationally recognised research hub for a sustainable and equitable world. Our goal is to help societies to transition to environmentally friendly and just conditions. At the core is the recognition that global environmental disruptions such as climate change, biodiversity loss, and resource depletion are closely linked with societal systems. To address these complex issues, we take a systemic approach and study the interconnectedness of human activities and the environment. Our mission is to develop sustainable, socially just, and environmentally friendly solutions by bridging disciplines and fostering collaboration between researchers, policymakers, and society.

The Economics of Sustainability (EoS) Group at LCSES is dedicated to advancing sustainability science through multi-scale economic analysis and modelling that incorporates the global-local-global interactions of agricultural input and output markets. Our team investigates the multifaceted relationships between economic systems and environmental change, with an emphasis on deploying innovative modelling frameworks for decision-making support at relevant scales.