Postdoctoral Fellowship in Advanced Computational Modelling of Deep Geological Facilities - KARAM
King Fahd University of Petroleum & Minerals (KFUPM)
in Partnership with the University of Manchester (United Kingdom)
Location: Dhahran, Saudi Arabia
Application Deadline: Open until filled
Start Date: As soon as possible
Duration: 2 years (extendable)
About the Position
The Interdisciplinary Research Center for Industrial Nuclear Energy (IRC-INE) at KFUPM is seeking a highly motivated Postdoctoral Researcher to join a cutting-edge project focused on supporting the long-term environmental safety of nuclear power generation and cogeneration in Saudi Arabia.
This position is a part of a strategic initiative with the University of Manchester (UK) under the KFUPM Advanced Radioactive waste disposal Alliance with the University of Manchester (KARAM). The mission is to support Saudi Arabia’s Vision 2030 energy diversity and sustainability goals by addressing the critical challenge of safely and permanently disposing of high-level radioactive waste.
The successful candidate will contribute to the development of advanced multi-physics simulation models to assess the long-term release and transport of radionuclides from deep geological facilities (DGF). They will also collaborate with other postdoctoral researchers: 1) investigating localized effects through discrete mesoscale modelling; and 2) developing machine learning-based risk assessment tools. These tools aim to simulate the complex degradation processes and interactions between geological and engineered barriers. The ultimate goal is to optimize DGF site selection, facility configuration, and material selection.
Key Responsibilities
- Develop and implement a fully coupled multi-physics finite element model for thermo-hydraulic-chemo-mechanical processes in deep geological facilities.
- Calibrate model parameters using experimental literature data and results from localized discrete simulations.
- Conduct parametric studies to evaluate the impact of hydrogeological, material, and design variables on long-term facility performance.
- Integrate machine learning algorithms for design optimization.
- Prepare scientific publications and conference presentations.
Qualifications
- A PhD in Engineering (Mech/Civil/Chem/Petro/Geo/Nuc/…) or a closely related discipline, with substantial experience in one or more of the following areas:
- Mechanics of materials and material degradation
- Reactive transport in fractured or porous media
- Thermo-hydraulic-chemo-mechanical modelling, particularly of clay-based materials
- Demonstrated expertise in multi-physics finite element modelling using tools such as COMSOL.
- Programming experience for developing custom plugins or user-defined functions in numerical simulation environments.
- Familiarity with machine learning methods for engineering applications is a plus.
- Excellent written and oral communication skills in English.
We Offer
- A dynamic, supportive research environment with skilled colleagues and excellent opportunities for scientific growth at one of the region's leading institutions.
- Opportunities to visit and collaborate with the University of Manchester.
- Access to cutting-edge computational resources and experimental facilities.
- A competitive salary and housing allowance.
- Benefits package, which includes: 30 days paid annual vacation, access to campus facilities and private beach, and campus medical service
How to Apply
Interested candidates should submit the following documents: irc-ine@kfupm.edu.sa
- Cover letter or research statement outlining research interests and fit for the position
- Full CV, including a list of publications
For more information about the position, please contact:
Pieter Boom
Email: pieter.boom@kfupm.edu.sa
Website: https://ri.kfupm.edu.sa/irc-ine
Help shape the future of safe sustainable nuclear energy—apply now!