PhD Student in AI & Sustainability Policy Lab – Computational Policy Analysis Interdisciplinary Transformation University (IT:U) in Austria

Interdisciplinary Transformation University (IT:U) in Austria invites applications for two PhD Student positions in the AI & Sustainability Policy Lab, part of the IT:U Doctoral School PhD Program COMPUTATIONAL X. The lab is dedicated to developing AI- and data-driven methods for designing, evaluating, and scaling effective climate and conservation policies. Research combines causal inference, behavioral economics, and machine learning to support evidence-based sustainability transitions addressing climate change and biodiversity loss.

PhD students will work collaboratively within a shared research agenda, pursuing complementary but independent topics. One position focuses on causal policy evaluation using econometric methods, field and survey experiments, and quasi-experimental research designs. The other emphasizes machine learning and AI methods for policy analysis, including causal machine learning, predictive modeling, and large-scale data integration. Research activities may include theory, modeling, surveys, experiments, and computational methods, often in international and interdisciplinary collaboration.

The lab offers collaborations with international partners in academia, policy institutions, and sustainability organizations. Interdisciplinary co-supervision is actively supported within IT:U and with external partners. Candidates benefit from international research exchanges, short-term research stays, and participation in international conferences. Structured mentoring in research design, publication strategy, grant writing, and science-to-policy translation is provided, emphasizing academic excellence, policy relevance, and transferable skills for diverse career paths.

Responsibilities include conducting research, publishing scientific papers, attending conferences, collaborating with other research groups, contributing to academic teaching (up to 2 weekly credit hours), supporting third-party funding applications, and adhering to academic standards and ethical guidelines.

Applicants must hold a master's degree (or equivalent) in economics, data science, computer science, statistics, public policy, or a related field. Strong quantitative and analytical skills, proficiency in programming (R or Python; Stata for economics-focused applicants), and experience with empirical research are required. Fluency in English (CEFR C1 or equivalent) is mandatory. Depending on the position, advanced knowledge of econometrics, behavioral economics, causal inference methods, policy design and evaluation, or machine learning and statistical modeling (including ML frameworks like PyTorch or TensorFlow) is expected. Experience with large-scale, geospatial, or text data, familiarity with causal machine learning, and demonstrated interest in climate change, biodiversity, or sustainability policy are strong assets.

The PhD program is structured over four years, with the first year focused on group work, research lab modules, and Project Integrated Courses (PICS), culminating in a PhD Proposal Presentation. Subsequent years involve thesis development, interdisciplinary seminars, and project assistant work, concluding with thesis submission and defense.

Funding includes a gross salary in line with FWF (EUR 2,832.10/month for 30h/week), optional supplementary contracts (teaching/research) up to 10 hours, and the Austrian KlimaTicket OÖ for unlimited public transport in Upper Austria. The positions are based in Linz, Austria, with innovative and stimulating working conditions in an international research environment.

To apply, submit your application via the online portal, including CV, diplomas, transcripts, motivational letter (max 2 pages), and up to 3 contacts for recommendations. Applications are reviewed on a rolling basis, and the call closes on 30 April 2026. Diversity and inclusion are strongly promoted; all qualified candidates are encouraged to apply.

For further information, contact Bettina Mairhofer (Teamlead for Student Administration) at [email protected].