Postdoc Position in Data-Driven Sustainability Policy and Economics

Das ist der Job

Excellent written and spoken English.

Darum lohnt es sich

The successful candidate will contribute to research at the intersection of AI, sustainability, and public policy, collaborating with an interdisciplinary team of economists, data scientists, and policy stakeholders.

Responsibilities Conducting high‑quality research activities Conducting academic teaching activities Preparing and publishing academic manuscripts in high‑impact academic journals Presenting research findings at national and international conferences Collaborating with other interdisciplinary research teams and external partners Supporting the preparation and submission of third‑party funding proposals Qualifications Completed PhD (or equivalent) in Economics, Data Science, Computer Science, Environmental Sciences, Political Science, Public Policy, or a related discipline with a quantitative focus.

Strong publication record relative to career stage, or clear potential to publish in leading international journals. Ability to work independently and collaboratively in interdisciplinary research teams. Collaborations with leading international researchers in sustainability, economics, and public policy.

Benefit from mentoring and support for developing an independent research profile. International mobility, conference participation, and exchange opportunities through our academic network. Additional Innovative and stimulating working conditions in an interdisciplinary, international research environment.

Flexible working hours through a flextime model and the option for home office. Company Description IT:U is a new technical university in Austria (Linz) dedicated to digital transformation, driven by interdisciplinary research and project-based learning to actively shape this transformation and advance it with a solution-oriented approach.

Department The AI & Sustainability Policy Lab uses quantitative methods to understand, evaluate, and scale effective climate and conservation policies. We combine causal inference, experimental/behavioral economics, machine learning, and computational social science to support evidence‑based sustainability transitions.

Climate change and biodiversity loss pose complex societal challenges that require both rigorous policy evaluation and advanced computational tools.

We are interested in generating credible causal evidence on the environmental, social, and economic impacts of climate and conservation policies, applying machine learning and AI to improve policy targeting, forecasting, prediction, and heterogeneous treatment effect estimation, and combining experimental methods, econometric analysis, and AI to generate and translate evidence for evidence‑based policymaking.

Understanding human behaviour, policy acceptance, and collective action in sustainability transitions through experimental and observational data is also a focus.

Strong expertise in one or more of the following areas: experimental and behavioural research methods, causal inference, econometrics and policy evaluation, machine learning, AI, and computational methods.

Research experience and demonstrated interest in sustainability, climate and environmental policy, biodiversity conservation, environmental governance or related policy domains. What you can expect Work on high‑impact research addressing climate and biodiversity challenges. Office kitchen with complimentary basic supplies.

Free parking or Climate Ticket Upper Austria. Compensation Competitive compensation starting from € 67,000 yearly gross salary.

How to Apply We look forward to receiving your online application (via the online portal below), including these elements: Cover letter, your CV, PhD certificate (or confirmation of expected completion date), one representative publication or working paper, and contact details of two references. #J-18808-Ljbffr