Job Details

Postdoctoral Fellowship in Design for Additive Manufacturing of Multifunctional Polymer Composites with Dual Radiation Shielding

King Fahd University of Petroleum & Minerals (KFUPM)

Interdisciplinary Research Center for Industrial Nuclear Energy (IRC-INE), in collaboration with the Research Center for Advanced Materials (IRC-AM)


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 invites applications for a Postdoctoral Fellowship within a funded three-year research project. The project will design, manufacture, and validate lightweight, load-bearing polymer composites that provide dual shielding against gamma and neutron radiation, for use in nuclear facilities, aerospace, and space systems where structural integrity and radiation protection are needed at the same time.

The material system is based on high-performance polymers (PEEK, PEI, and PPSU) reinforced with hybrid fillers: boron carbide (B4C) for thermal-neutron capture and gadolinium oxide (Gd2O3) for combined neutron and gamma attenuation, with titanium dioxide (TiO2) and boron nitride (BN) to improve dispersion, toughness, and thermal stability. Components are produced by material-extrusion additive manufacturing using Design for Additive Manufacturing (DfAM) principles, including topology and lattice optimization.

The successful candidate will lead the characterization and data-analytics activities of the project, developing machine-learning models coupled with multiphysics and radiation-transport simulations to predict process–structure–property–shielding relationships, and will support prototype fabrication and validation under mixed gamma–neutron fields. The work is carried out by an interdisciplinary team spanning nuclear engineering, advanced materials and additive manufacturing, and experimental radiation measurement.

 

Key Responsibilities

The successful candidate will:

  • Perform advanced characterization of compounded filaments and printed composites, including microstructure and dispersion (SEM, XRD), thermal behavior (TGA, DSC), porosity and internal defects (micro-CT), and mechanical testing (tensile and flexural per ASTM D638/D790, compression, and fatigue)
  • Compile and manage a combined experimental and simulation database linking process parameters and filler content to strength, porosity, and radiation attenuation
  • Develop and train supervised machine-learning models (e.g., Random Forest, SVR, Gradient Boosting) to predict mechanical and shielding performance, with feature-importance, sensitivity, cross-validation, and uncertainty analyses.
  • Couple machine-learning models with finite-element simulations of thermal and mechanical fields during printing (e.g., COMSOL or ABAQUS) and with Monte Carlo radiation-transport simulations (e.g., MCNP or FLUKA), contributing to a digital-twin framework of composite behavior
  • Support DfAM optimization of lattice and graded architectures and printing parameters (layer height, raster angle, infill density, temperature) using Design of Experiments.
  • Assist in gamma and neutron attenuation measurements and in evaluating performance degradation after thermal aging and radiation exposure
  • Contribute to prototype fabrication and validation of multifunctional composite panels and structural inserts
  • Co-supervise graduate and undergraduate students and support project reporting
  • Publish results in high-impact peer-reviewed journals, present at international conferences, and contribute to invention disclosures
Qualifications

Applicants must hold a PhD in Mechanical, Materials, Chemical, Polymer, or Nuclear Engineering, or a closely related field, with substantial experience in one or more of the following:

  • Polymer composite processing and fabrication
  • Additive manufacturing (material extrusion/FDM), preferably with high-performance thermoplastics
  • Materials characterization and mechanical testing of polymer composites
  • Machine learning and data analytics for materials or process–property prediction
  • Multiphysics or finite-element modeling (e.g., COMSOL, ABAQUS, ANSYS)

    Proficiency in programming for data analysis and model development (e.g., Python or MATLAB) and a strong publication record in peer-reviewed journals are essential.

    Desirable

  • Experience with gamma/neutron shielding measurements or Monte Carlo radiation-transport codes (e.g., MCNP, FLUKA, Geant4)
  • Experience with topology optimization or lattice design for additive manufacturing
  • Experience with filler surface modification and polymer compounding (twin-screw extrusion)
We Offer

KFUPM offers a dynamic and supportive research environment, including:

  • Competitive salary and housing allowance
  • 30 days paid annual vacation
  • Campus medical care
  • Access to campus facilities, including private beach access
  • Advanced additive manufacturing, characterization, and computational facilities
  • Collaboration within an interdisciplinary team in nuclear engineering, advanced materials, and radiation measurement
How to Apply

 

Interested candidates should send the following documents to irc-ine@kfupm.edu.sa and belal.momani@kfupm.edu.sa, quoting the position title in the email subject:

  • Cover letter and research statement describing relevant experience and interest in the position
  • Full CV including a complete list of publications

Applications will be reviewed on a rolling basis until the position is filled.

For inquiries about the position, please contact Dr. Belal Al-Momani, Assistant Professor, Mechanical Engineering Department, KFUPM: belal.momani@kfupm.edu.sa

Website: ri.kfupm.edu.sa/irc-ine