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Most of the flood prone cities around the world relay on natural and man-made flood defences to protect themselves against coastal and riverine flood events. While many of the deterioration mechanisms which may compromise the stability of these structures are well understood, backward piping erosion is still one of the most difficult failure mechanisms to model and predict making it one the biggest threats for flood defence systems. The two main reasons for this are that a) flood defence structures such as dikes are often funded over highly heterogeneous soil systems which are difficult to represent and b) the available computational models for correctly representing the process and its inherited heterogeneities are still highly computationally demanding. Significant numerical advances, systems safety assessment studies and case databases are already available regarding backward piping erosion in dikes but there is still a big knowledge gap in how to combine and harmonize these data sets and models to produce more robust methods for its deterministic and probabilistic assessment. In the actual state of the art of machine learning, methods like semi-supervised learning, deep learning and reinforces learning open a window of opportunities to produce more robust models when combining multiple sources of information.
For these reasons, the PhD intended research aims to improve the modelling and probabilistic prediction of piping erosion by combining detailed physically based models with other sources of information with the help of machine learning techniques so that piping erosion modelling accuracy and detail are improved while making them computationally feasible for probabilistic assessment of dike safety against backward piping erosion. It is expected that the actual state of the art for better representing this failure mechanism will significantly improve while making it more accessible for the actual hydraulic and geotechnical engineering by developing open-source codes and robust design rules.
The project will be developed as part of the research lines of the Hydraulic Structures and Flood Risk section in the Hydraulic Engineering department at TU Delft, under the supervision of Dr. Juan Pablo Aguilar-López and Prof. Dr. Bas Jonkman. Throughout the project, you will be given the opportunity to work with leading academic and industrial partners, both in the Netherlands and abroad.
We are looking for an excellent candidate with the following qualifications, knowledge and skills:
Fixed-term contract: 4 years.
TU Delft offers PhD-candidates a 4-year contract, with an official go/no go progress assessment after one year. Salary and benefits are in accordance with the Collective Labour Agreement for Dutch Universities, increasing from € 2395 per month in the first year to € 3061 in the fourth year. As a PhD candidate you will be enrolled in the TU Delft Graduate School. The TU Delft Graduate School provides an inspiring research environment with an excellent team of supervisors, academic staff and a mentor. The Doctoral Education Programme is aimed at developing your transferable, discipline-related and research skills.
The TU Delft offers a customisable compensation package, discounts on health insurance and sport memberships, and a monthly work costs contribution. Flexible work schedules can be arranged. For international applicants we offer the Coming to Delft Service and Partner Career Advice to assist you with your relocation.
Delft University of Technology is built on strong foundations. As creators of the world-famous Dutch waterworks and pioneers in biotech, TU Delft is a top international university combining science, engineering and design. It delivers world class results in education, research and innovation to address challenges in the areas of energy, climate, mobility, health and digital society. For generations, our engineers have proven to be entrepreneurial problem-solvers, both in business and in a social context. At TU Delft we embrace diversity and aim to be as inclusive as possible (see our Code of Conduct). Together, we imagine, invent and create solutions using technology to have a positive impact on a global scale.
Challenge. Change. Impact!
The Faculty of Civil Engineering & Geosciences (CEG) is committed to outstanding international research and education in the field of civil engineering, applied earth sciences, traffic and transport, water technology, and delta technology. Our research feeds into our educational programmes and covers societal challenges such as climate change, energy transition, resource depletion, urbanisation and the availability of clean water, conducted in close cooperation with a wide range of research institutions. CEG is convinced that Open Science helps to achieve our goals and supports its scientists in integrating Open Science in their research practice. The Faculty of CEG comprises 28 research groups in the following seven departments: Materials Mechanics Management & Design, Engineering Structures, Geoscience and Engineering, Geoscience and Remote Sensing, Transport & Planning, Hydraulic Engineering and Water Management.
Click here to go to the website of the Faculty of Civil Engineering & Geosciences.
Delft University of Technology (TU Delft)
Mekelweg 2, 2628 CD, Delft
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