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

Interdisciplinary Transformation University (IT:U) in Linz, Austria, offers two PhD positions in the AI & Sustainability Policy Lab as part of its Doctoral School PhD Program COMPUTATIONAL. 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 complex challenges such as climate change and biodiversity loss.

PhD students will pursue complementary but independent topics within a shared research agenda. 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 collaborates with international partners in academia, policy institutions, and sustainability organizations. Doctoral students benefit from international research exchanges, short-term research stays, and participation in conferences. Structured mentoring is provided in research design, publication strategy, grant writing, and science-to-policy translation. The program emphasizes academic excellence, policy relevance, and transferable skills for careers in academia, public institutions, or the private sector.

Responsibilities include conducting research, publishing scientific papers, attending conferences, collaborating with 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 have 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 is an advantage), and experience with empirical research are required. Fluency in English (CEFR C1 or equivalent) is mandatory. Depending on the position, expertise in applied econometrics, behavioral economics, causal inference methods, policy design and evaluation, machine learning, statistical modeling, and ML frameworks (PyTorch or TensorFlow) is expected. Experience with large-scale, geospatial, or text data and familiarity with causal machine learning are strong assets. Demonstrated interest in climate change, biodiversity, or sustainability policy is highly valued.

The program offers innovative working conditions in an interdisciplinary, international environment, complimentary office kitchen supplies, and the Austrian KlimaTicket OÖ for unlimited public transport in Upper Austria. The gross salary is EUR 2,832.10/month (30h/week), with optional supplementary contracts for teaching or research up to 10 hours. The structured 4-year PhD program includes group work, lab modules, project integrated courses, proposal presentation, thesis development, research seminars, and project assistant work, concluding with thesis submission and defense.

To apply, fill in the online application form and upload your CV, diplomas, transcripts, motivational letter (max 2 pages), and up to 3 contacts for recommendations. The positions remain open until filled, with a final deadline of 30 April 2026. Diversity and inclusion are actively promoted. For questions, contact Bettina Mairhofer ([email protected]).