PhD Candidate - Generative Agent-Based Modeling for Climate Policy Design

• Education: MSc degree in Computer Science, Operations Research, Data Science, Industrial Engineering, Computational Social Science, or a closely related field.
• Technical Skills:
• Solid background in computational modelling, simulation, or optimization techniques.
• Programming proficiency in Python (experience with LLM frameworks, prompt engineering, or agent-based frameworks is a strong plus).
• Familiarity with machine learning, Large Language Models (LLMs), or natural language processing.
• Soft Skills: Strong analytical problem-solving abilities, excellent writing skills for scientific publications, and the ability to work independently within a multidisciplinary team.

We recognize that candidates may have different academic and professional backgrounds. If you do not meet all of the requirements but believe that your skills, experience, and motivation make you a strong potential candidate, we still encourage you to apply. We look forward to hearing from you.

Provisions relating to positions as PhD Research Fellows can be found in the Applied Engineering program web page.

Fully Funded PhD Opportunity at TECNUN, the School of Engineering of the University of Navarra, Spain

We are seeking a highly motivated PhD Researcher to join our team for a 3- to 4-year fully funded PhD opportunity. The successful candidate will work at the intersection of Artificial Intelligence, Operations Research, and Policy Modelling to build advanced decision-support tools for climate action and disaster resilience.

The candidate will be part of the Resilience research group at TECNUN, which focuses on understanding and strengthening the resilience of communities, cities, and organizations in the face of disruptions and crises. The group combines engineering, data-driven approaches, and decision-support methodologies, with research spanning areas such as urban resilience, crisis management, infrastructure, and emerging technologies such as AI and LLMs.

The PhD candidate will join this research environment under the supervision of Professor Josune Hernantes and Dr. Sahar Elkady.

This PhD project focuses on developing a novel decision-support framework that combines Generative Agent-Based Modelling (GABM) with Simulation Optimization. The primary goal is to simulate how diverse societal stakeholders (e.g., citizens, businesses, and public authorities) interact, perceive, and respond to climate-related policies. By integrating LLM-driven generative agents into an optimization loop, the project aims to help decision-makers design robust policies that balance environmental targets with public acceptance and social legitimacy.

The PhD candidate will conduct research leading to the development of their doctoral thesis, with the aim of disseminating their findings through high-quality publications in highly ranked, internationally recognized journals. The candidate will be expected to take an active role in the development and execution of research projects related to their research topic, as well as contribute to the preparation and submission of research proposals and funding applications.

The candidate should also be willing to actively participate in seminars, workshops, meetings, and other activities organized by the Department and the research group. As part of the responsibilities established in the PhD student agreement, the candidate will be expected to contribute to teaching activities, including serving as a teaching assistant in selected courses and proctoring examinations. These responsibilities are intended to provide the candidate with broader academic and professional development alongside their research activities.