PhD Optimizing evacuation decisions under infrastructure failure

Role Overview:
Climate change is rapidly increasing the frequency and severity of extreme weather events. The Netherlands, where 26% of the territory lies below sea level, is particularly vulnerable to flooding and other climate-related hazards. Effective a priori evacuation plans are known to reduce loss of life, yet uncertainty surrounding both the spatial development and temporal progression of disasters often renders theoretically optimal evacuation decisions unviable in practice. Designing evacuation strategies that remain efficient, feasible and resilient when critical infrastructure is threatened by large-scale disruptions therefore remains a major challenge in Operations Research. The RESCUE project develops new multi-stage optimization models for pre-disaster evacuation decisions on critical road and shelter infrastructure subject to failures. Combining robust optimization, stochastic programming and copula theory, the project assesses the resilience of both self-evacuation and shelter-in-place strategies. For this purpose, the project draws on concepts from network flow problems and assignment problems. Models are validated using hydrodynamic simulations of Dutch flash flood scenarios.

Responsibilities:
Your duties include:
- Conduct high-quality doctoral research leading to journal articles and a PhD dissertation.
- Develop optimization models, algorithms, and computational methods for robust evacuation planning.
- Present your work at scientific conferences and workshops with academic and industry partners.
- Participate in PhD training courses, with the opportunity to obtain a PhD teaching qualification certificate.
- Contribute to the teaching activities of the department (lectures, tutorials, exams, grading, etc.).
- Work closely with the supervisory team and help translate results into practical recommendations for disaster preparedness.

Requirements:
- A master’s degree in Operations Research, Computer Science, Applied Mathematics, Econometrics, Industrial Engineering, or a closely related field with a strong quantitative component.
- Strong interest in optimization, mathematical programming and computational methods.
- Prior knowledge of stochastic programming or (distributionally) robust optimization is an advantage.
- Affinity with network resilience, climate resilience, or flood risk applications is also a plus.
- Strong programming skills in any (object-oriented) programming language.
- Prior experience with optimization solvers (Gurobi or CPLEX) and simulation tools is an advantage.
- Strong analytical writing skills and the ability to present technical results clearly.
- Excellent command of English in both speaking and writing.

Qualifications:
- A master’s degree in a relevant field with a strong quantitative component.
- Strong background in optimization, mathematical programming, and computational methods.
- Experience with stochastic programming or (distributionally) robust optimization.
- Proficiency in programming languages and optimization solvers.
- Excellent analytical and communication skills.
- Fluency in English.

What They Offer:
- A challenging position in a socially engaged organisation.
- A salary of € 3.059,00 (PhD) and maximum € 3.881,00 (PhD) gross per month in the fourth year, for a full-time employment.
- An employment contract of initially 1 year, which may be extended to a total of 4 years if there is sufficient perspective.
- Attractive fringe benefits and arrangements, including a full-time 38-hour working week with a holiday leave entitlement of 232 hours per year.
- 8% holiday allowance and 8.3% end-of-year bonus.
- Solid pension scheme (ABP).
- Contribution to commuting expenses.
- Optional model for designing a personalized benefits package.