As a PhD candidate, you will develop quantitative mathematical and computational models that connect individual attitudes and decision-making to collective behaviour change. Your work will focus on identifying conditions under which small interventions can scale into large, self-sustaining transitions (social tipping dynamics), and when such dynamics may stall or reverse. You will connect qualitative to quantitative theories by working closely with the ROOTS team and collaborating with societal partners to keep the research policy-relevant and grounded in real-world constraints.

You are expected to focus on your PhD research and take an active role in departmental activities, ranging from participating and organizing research and education seminars, group activities, to grant applications.

Tasks and responsibilities:

The list of tasks is not exhaustive and covers some aspects of both positions. If there are sets of skills that you already have or would like to develop or a topic that you are particularly interested, please mention those in your motivation.

• Derive behavioural models from individual-level data
• Develop mean-field, agent-based, and network-based models of collective behaviour adoption with heterogeneous preferences and reversible dynamics
• Link individual-level factors (e.g., costs, norms, infrastructure, trust) to adoption outcomes in the domains of technology adoption (e.g., solar PV) and/or daily behavioural choices
• Contribute to the design and analysis of discrete-choice (conjoint) experiments and survey measures that parameterize and validate the models
• Derive interpretable outputs for policy partners (e.g., elasticity curves, scenario analyses, “what-if” intervention tests)
• Publish results in peer-reviewed journals
• Present at international conferences
• Participate in team activities at CSL and POLDER/IAS (workshops, seminars) and contribute to collaborative papers
• Assist in teaching and supervision (e.g., tutorials, MSc/BSc projects) in consultation with the group within the programmes MSc Computational Science and MSc Complex Systems and Policy

• An MSc (or equivalent) in computational social science, applied mathematics, physics, computer science, behavioural science, econometrics, or a closely related field
• You can translate messy real-world questions into clear model assumptions and testable mechanisms
• Demonstrable experience with quantitative analysis and programming (e.g., Python and/or R)
• You communicate clearly in spoken and written English and can write publishable academic texts
• You collaborate well in an interdisciplinary team and are motivated to engage with societal stakeholders
• It is a preference if you additionally have experience with discrete-choice modelling, complex contagion/threshold models, computational economics, causal discovery, and/or simulation-based inference.

A temporary contract for 38 hours per week for the duration of 4 years (the initial contract will be for a period of 18 months and after satisfactory evaluation it will be extended for a total duration of 4 years). The preferred starting dates are September 2026 and September 2027, for each of the two PhD positions. This should lead to a dissertation (PhD thesis). We will draft an educational plan that includes attendance of courses and (international) meetings. We also expect you to assist in teaching undergraduates and master students.

The gross monthly salary, based on 38 hours per week and dependent on relevant experience, ranges between € 3,059 to € 3,881 (scale P). This does not include 8% holiday allowance and 8,3% year-end allowance. The UFO profile PhD Candidate is applicable. A favourable tax agreement, the ‘30% ruling’, may apply to non-Dutch applicants. The Collective Labour Agreement of Universities of the Netherlands is applicable.

Curious about our extensive secondary benefits package? You can read more about it here.