DC06: High-performance multi-phase, volume-coupled material point method for modelling submarine landslides

DC06: High-performance multi-phase, volume-coupled material point method for modelling submarine landslides

Published Deadline Location
11 Jan 15 Mar Enschede

Job description

We are seeking a full time PhD researcher with interests in granular physics, computer modelling and Machine Learning techniques to join University of Twente (Netherlands), and work on a novel high-performance multi-phase material point method for modelling submarine landslides .
This project is part of the EU funded Marie Curie Doctoral Network POSEIDON – Improve offshore infrastructure resilience against geohazards towards a changing climate (www.poseidon-dn.eu). The overarching objective of POSEIDON is to develop, solutions to improve the resilience of offshore infrastructures. POSEIDON will train 13 researchers within a collaborative multidisciplinary and inter-sectorial network involving 9 universities, 3 research institutes and 4 industrial partners across Europe.

Background and aim:
Submarine landslides involve the movement of saturated sediments down a slope, interacting with seawater and/or offshore infrastructure. During landslides, the bulk of the sediment material (usually considered as a porous medium), transits from solid-like to fluid-like, i.e., from stagnant to continuously flowing. In addition, the coupling between seawater and sediment is crucial in the landslide dynamics. Recent studies have shown that the material point method (MPM) can describe the movement of saturated sediment and the hydrodynamic coupling between soil skeleton and seawater, within a multiple-phase framework. Nevertheless, to accurately predict the dynamics of and dissipation within the sliding masses, the transition between solid and flowing states of sediments must be incorporated.

The doctoral candidate will implement constitutive models for saturated sediments in fluid- and solid-like states into an existing GPU-MPM code. The exchange of momentum, mass, and energy between these admissible states of saturated sediments will be achieved with overlapping subdomains where the transition can potentially take place. To further improve the computational efficiency, machine learning surrogates will be used to partially replace the expensive physics-based models to allow large-scale industrial applications. The project aims to provide more accurate, highly efficient, and physics-based predictions for submarine landslides in order to quantitively assess the risk of damages to offshore infrastructures (e.g., foundations anchors) and induced disasters (e.g., tsunamis).

i) Extend an existing MPM code from single-phase to multi-phase based on a volume-coupled formulation that incorporates mass, momentum, and energy exchange between slow- and fast-flowing sediments and water;

ii) Develop a reduced-order model of the multi-phase system using machine learning and integrate it into the volume-coupled numerical framework;

iii) Perform simulations of submarine landslides and assess their impact on offshore infrastructures;

iv) Calibrate model parameters using existing experimental data and compare the model predictions with experimental data obtained from laboratory flume experiments.

Expected Results:
i) A novel volume-coupled formulation to consider the transport and coupling of multiple phases;

ii) An open-source, multi-phase GPU-based MPM code with clear documentation, tutorials, and examples for future users;

iii) Benchmark cases validated using experimental data from laboratory-scale physical tests.

Planned Secondment(s):
Dr. Michele Larcher (Free University of Bolzano, 2 months): Perform a laboratory-scale experiment on slope collapse and its interaction with foundation anchors in the flume device; the movement of sediment transport underwater will be recorded and analysed to validate the multiphase MPM model for submarine landslides. DC06 will build his/her work on the experiments previously performed by DC03 in UNIBZ.

Dr. Xue Zhang (University of Liverpool, 3 months): Improve the parallelization of the MPM code; incorporate structural mechanics into the code, e.g., using the finite element method, towards assessing the impact of the slides on submarine infrastructures; comparison of PFEM-MPM methods performances.


University of Twente (UT)


  • Obtained a MSc degree in a relevant field such as civil engineering, mechanical engineering, computational physics, applied mathematics, materials science, or related areas
  • Experience with numerical methods for solving partial differential equations;
  • Previous experience with multi-phase materials and transport phenomena and/or deep neural network solvers will be advantageous;
  • Sound programming skills in C/C++, Fortran, Python or equivalent;
  • You are an excellent teammate, able to collaborate intensively with industrial and academic parties in regular meetings and work visits;
  • An appropriate qualification in the English Language together with excellent communication and organizational skills.

We are an equal opportunity employer and value diversity at our company. We do not discriminate on the basis of race, religion, color, national origin, gender, sexual orientation, age, marital status, or disability status. Women are explicitly asked to apply for this position. This is part of the University of Twente’s strategy to increase the proportion of women among its faculty and to create a working environment that is diverse and inclusive and supportive of excellence in research and education.

Conditions of employment

We offer you a very exciting position in an inspiring multidisciplinary environment. The university offers a dynamic ecosystem with enthusiastic colleagues in which internationalization is an important part of the strategic agenda.
  • We offer a full-time 4-year PhD-position, with excellent mentorship and a stimulating research environment.
  • Collaborations with a dedicated, dynamic research team and external parties from several European countries involved in the POSEIDON project.
  • The gross monthly salary will be ranging from € 2.770,00 (first year), increasing each year up to € 3.539,00 in the fourth year. Salary and associated conditions are in accordance with the collective labour agreement for Dutch universities (CAO-NU).
  • You will have a minimum of 232 leave hours in case of full-time employment based on a formal workweek of 38 hours.
  • A full-time employment in practice means 40 hours a week, therefore resulting in 96 extra leave hours on an annual basis.
  • We offer excellent fringe benefits including a holiday allowance of 8% of the gross annual salary, an end-of-year bonus of 8.3%, a solid pension scheme, free access to sports facilities and a family-friendly institution that offers parental leave (both paid and unpaid).

The University of Twente is situated on a green and lively campus with lots of facilities for sports and other activities.

Additional information

As a PhD candidate, you will be enrolled in the University of Twente. The Ph.D project will be conducted under the supervision of prof. V. Magnanimo, prof. S. Luding and dr. Hongyang Cheng. An extended Supervisory Committee, including academic and industrial supervisors from The POSEIDON consortium, will guide the candidate during his/her PhD.

Please submit your application before 15 March 2024 via the ‘Apply now’ button, including:
  • Cover Letter: A maximum of two A4 pages, highlighting your specific interest in the position, your qualifications, and motivations for applying. This letter should clearly articulate how your background and experiences align with the requirements of this project
  • Detailed Curriculum Vitae (CV): The CV, should include, if applicable, a list of publications;
  • Bachelor and Master transcripts;
  • Contact Details of Referees: Provide the names and contact information of individuals who can professionally vouch for your qualifications and suitability for this position.

Master students who will graduate in the next coming months are welcome to apply. In that case, please provide an overview of the transcripts that are already available.

The deadline for application is 15 March 2024. The intended starting date is 1 September 2024, at latest.

You are welcome to contact prof. dr. Vanessa Magnanimo (email v. magnanimo@utwente.nl) or dr. Hongyang Cheng (email: h.cheng@utwente.nl) for any questions you might have.

The first round of selection interviews is scheduled few weeks after the closure of the applications and interviews can be held through Microsoft Teams. A second round of interviews may be scheduled if necessary.


  • PhD
  • Engineering
  • max. 38 hours per week
  • €2770—€3539 per month
  • University graduate
  • 1609


University of Twente (UT)

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Drienerlolaan 5, 7522NB, Enschede

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Application procedure

Application procedure

Make sure to apply no later than 15 Mar 2024 23:59 (Europe/Amsterdam).