University:
Delft University of Technology
Country:
Netherlands
Deadline:
2025-09-26
Fields:
Environmental Science, Environmental Engineering, Hydrogeology, Physics, Applied MathematicsHow can advanced surrogate modeling and uncertainty quantification revolutionize the way we predict and manage groundwater quality in a changing world?The increasing complexity of environmental challenges, such as safeguarding groundwater quality, demands innovative computational approaches. If you are passionate about applying machine learning, statistics, and environmental modeling to real-world issues, the PhD position in Surrogate-enabled Uncertainty Quantification for Reactive Transport Modeling at Delft University of Technology (TU Delft) in the Netherlands offers a unique opportunity to contribute to water safety and sustainability on a global scale.
About The University Or Research Institute
Delft University of Technology (TU Delft) is one of Europe’s leading technical universities, renowned for its cutting-edge research and innovation in science, engineering, and design. Located in Delft, a historic city in the heart of the Netherlands, TU Delft has a longstanding reputation for excellence in education and research, particularly in fields related to water management, civil engineering, and environmental sciences.The university’s Faculty of Civil Engineering & Geosciences (CEG) is dedicated to advancing knowledge in civil engineering, applied earth sciences, traffic and transport, water technology, and delta technology. TU Delft’s vibrant international community, commitment to open science, and strong industry and academic partnerships make it a prime destination for ambitious researchers. The Netherlands itself is globally recognized for its expertise in water management and environmental innovation, offering an ideal setting for research that addresses pressing societal challenges.International students at TU Delft benefit from comprehensive support services, including the Coming to Delft Service, which assists with relocation, integration, and career development for both researchers and their families. The university’s inclusive academic environment, diverse student body, and location in a safe, welcoming country make it an excellent place to pursue doctoral studies and build a global network.
Also See
- Netherlands – PhD in Surrogate Modeling for Groundwater at Delft University of Technology
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- Canada – PhD/Postdoc in Numerical Optimization at Polytechnique Montréal
Research Topic and Significance
The focus of this PhD project is on developing surrogate-enabled uncertainty quantification frameworks for reactive transport modeling in groundwater systems. Reactive transport models are vital for assessing groundwater quality and contamination risks, which are critical for ensuring safe drinking water supplies worldwide. However, the accuracy of these models is often limited by uncertainties in parameters and data, and traditional Bayesian uncertainty quantification methods can be prohibitively computationally expensive for complex systems.By leveraging surrogate modeling—creating efficient approximations of computationally intensive models—and integrating advances in machine learning, this project aims to enable robust uncertainty quantification even within limited time and resource budgets. The outcomes will provide more reliable predictions and risk assessments for groundwater quality, thereby supporting safer and more sustainable water management practices. The research will have direct impact on public health, environmental protection, and policy-making related to water resources.
Project Details
The PhD candidate will join a multidisciplinary team at TU Delft, collaborating closely with the AIdroLab (part of TU Delft AI) and the Statistical Model-Data Integration group at the University of Stuttgart. The project bridges hydrogeology, biogeochemistry, statistics, and machine learning, focusing on both methodological advances and practical applications in water quality modeling.
Key Responsibilities Include
– Designing and implementing surrogate modeling strategies for efficient uncertainty quantification of reactive transport models.– Evaluating and propagating surrogate model errors to improve uncertainty estimates.– Applying the developed framework to real-world case studies in collaboration with international working groups in water quality modeling.The department is recognized for its expertise in water quality, environmental system modeling, and the integration of statistical and machine learning techniques in water resources research.
Candidate Profile
Ideal Applicants For This Position Will Have
– A Master’s degree in environmental science, environmental engineering, hydrogeology, physics, applied mathematics, or a related discipline.– A strong interest in uncertainty quantification, Bayesian statistics, and machine learning; demonstrable experience in at least one of these areas is considered an advantage.– Familiarity with numerical modeling and scientific programming (e.g., Python, Julia, or R).– Preferably, experience in modeling reactive transport in groundwater.– Excellent written and spoken English, suitable for working in an international academic environment.– Enthusiasm for interdisciplinary research, particularly at the interface of hydrogeology, statistics, and computational modeling.TU Delft requires all PhD candidates to meet English proficiency standards to ensure effective communication, participation in doctoral education, and successful completion of research outputs.
Application Process
Delft University of Technology is a top-tier institution, offering doctoral candidates a four-year employment contract (structured as an initial 1.5-year contract with a progress assessment, followed by a further 2.5 years upon satisfactory performance). The salary ranges from €3059 per month in the first year to €3881 in the fourth year, in line with the Collective Labour Agreement for Dutch Universities. Additional benefits include a customizable compensation package, health insurance discounts, flexible work schedules, and support for international relocation and dual-career partners.To Apply, Candidates Must Submit Their Applications Online (applications By Email Or Post Will Not Be Processed) By 26 September 2025. The Application Should Include– A motivation letter (maximum one page).– A 1-2 page CV, including names and contact information for two references.– Copies of academic transcripts (with grades for all courses).– An individually authored scientific text (such as an MSc thesis or course report in English).Interviews are expected to take place in early October 2025. Please note that a pre-employment screening and a knowledge security check (as per Dutch National Knowledge Security Guidelines) may form part of the selection process.For further details and to apply, visit the official position page:https://careers.tudelft.nl/job/Delft-PhD-Position-Surrogate-enabled-Uncertainty-Quantification-for-Reactive-Transport-Modeling-2628-CD/805694202
Conclusion
This PhD position at TU Delft represents an exceptional opportunity for motivated researchers to advance the field of uncertainty quantification in environmental modeling while contributing to the global challenge of ensuring safe water resources. If you are eager to develop innovative computational methods and collaborate within a world-class research community, consider applying to join TU Delft’s renowned Faculty of Civil Engineering & Geosciences. Stay informed about similar opportunities by following updates on leading academic job platforms.Want to calculate your PhD admission chances? Try it here:https://phdfinder.com/phd_admission_chance_calculator/
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