Job description

Background:

Globally adaptation to climate change remains both critical and urgent. The momentum to act is rising and empirical evidence is growing. Yet, we still lack systematic ex-ante and ex-post quantitative assessments of adaptation effectiveness and limits across various scales (temporal, spatial, decision) and contexts (exposure to different hazards, or institutional and cultural factors). This limited knowledge hinders a full understanding of societal progress on adaptation worldwide, and in Europe in particular. Since adaptation effectiveness is highly location- and context-specific we need a systematic comparison across cases. This PhD position is part of the European project ADELE, which aims to make progress in assessing adaptation effectiveness and limits. As part of a team of 20 institutions, TU Delft will contribute to ADELE by: (1) collecting primary quantitative data on household autonomous adaptation to climate induced hazard, provide new evidence of soft and hard limits, and undertake ex-ante and ex-post assessments of adaptation effectiveness; (2) advancing analytical methods—including structured households’ surveys and Agent-Based Modeling (ABM)—for the quantification of adaptation effectiveness and limits. The overall outcomes of the ADELE project will contribute to the ongoing EU Commission and the European Environmental Agency efforts on climate adaptation, including EUCREA2, European Climate Adaptation Plan and integrated framework for European climate resilience and risk management, as well as IPCC.

Job description:

Over the 4-year trajectory, the successful candidate will conduct impact-focused research bridging empirical survey data with advanced computational modeling. Your main responsibilities will be shared between two main research activities (approximately 70%-30%):

1. Large-Scale Survey Development & Data Analysis for Ex-Post Assessment: Develop and deploy a structured household survey to evaluate the (perceived) effectiveness of past and ongoing private adaptation across 3 European countries. Depending on the case, we will focus on adaptation to key climate-induced hazards: heatwaves, wildfires, droughts, floods, and sea level rise. Relying on the existing expertise in our team and state-of-the art surveys, the PhD student will lead the development of the household survey and analyze data to assess the conditions for "soft limits" (behavioral, economic, social, institutional) that hinder private adaptation. The goal is to elicit empirical evidence on the adaptation constraints such as income differentials, risk awareness, self-efficacy, social norms, and self-perceived vulnerability. Potential collaboration: you will get an opportunity to work closely with a sister institution in Italy, exchanging insights and questions with their team developing parallel surveys for firms.

2. Agent-Based Modeling (ABM) & Ex-Ante Assessment: Translate the empirical evidence from your surveys into modular ABM components to study adaptation effectiveness over time and explore when household adaptation limits are reached. The PhD student will leverage existing in-house ABMs at TU Delft (e.g. EMERGO, CRAB, FAST) that can be applied at different spatial scales (urban to national) to project the uptake of private adaptation measures under multiple hazards and constraints. ABM permit comparative analyses of adaptation effectiveness, avoided economic losses and damages, and distributional impacts across society. By applying household survey data from different European cases, we can advance the development of private household adaptation module as a standardized, interoperable building block. This effort will contribute to open science by sharing empirically-verified software modules via www.agentblocks.org, allowing the broader international climate modeling community to integrate these ready-made components.

Job requirements

We are looking for a motivated and collaborative researcher. The ideal candidate possesses:

• A Master’s degree in Environmental Economics, Psychology, Complex Systems, Engineering & Policy Analysis, or a related field;
• Experience with data analysis and statistical methods;
• A strong interest in developing, conducting, and analyzing surveys;
• Experience with Agent-Based Modeling (ABM) or at least programming skills in a scientific language (Python, Julia, etc.);
• Domain interest in climate change impacts, climate adaptation or in general in coupled social–environmental systems is an advantage;
• Teamwork and communication skills, with the ability to collaborate effectively in an international, multidisciplinary research project;
• Fluent written and spoken English.

TU Delft (Delft University of Technology)

Working at TU Delft means contributing to solutions that really make a difference.

For over 180 years, we have been training engineers who make an impact worldwide in companies, government bodies, or as entrepreneurs. Our alumni turn knowledge into concrete solutions for the challenges of today and tomorrow. These challenges are changing rapidly. That is why we focus on themes such as energy, climate, digitalisation, artificial intelligence (AI), and smart mobility every day. Our education and research are directly aligned with what society needs now and in the future.

At TU Delft, our people make the difference. With their knowledge and curiosity, our staff provide a high-quality education and conduct pioneering research that extends beyond the campus. You will have the opportunity to take the initiative, work with others, and grow as a professional. Working at TU Delft means join an international community of professionals and students. Together, we create knowledge, innovations, and solutions that help move the world forward.

Faculty Technology, Policy & Management

The Faculty of TPM provides an important contribution to solving complex technical-social issues, such as energy transition, mobility, digitalisation, water management and (cyber) security. TPM does this with its excellent education and research at the intersection of technology, society and policy. We combine insights from both engineering and social sciences as well as the humanities. TPM develops robust models and designs, is internationally oriented and has an extensive network of knowledge institutions, companies, social organisations and governments.

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