Postdoctoral Fellow / Research Assistant in Computational Radiation Physics and AI at UAEU, UAE

The Department of Physics at the United Arab Emirates University (UAEU) is inviting applications from qualified and motivated candidates for a Research Assistant or Postdoctoral Research Fellow position in Computational Radiation Physics and AI Surrogate Modeling. Funded by the Federal Authority for Nuclear Regulation (FANR), this project provides a unique opportunity to work at the intersection of nuclear engineering, scientific computing, radiation transport, and physics-informed machine learning.

Position Overview

Project Description & Summary

The successful applicant will contribute to a cutting-edge, FANR-funded research initiative focused on creating physics-informed artificial intelligence (AI) surrogates for rapid radiological dose assessment and radiation transport modeling. By bridging high-fidelity Monte Carlo radiation transport simulations (such as MCNP and GEANT4) with state-of-the-art AI and Physics-Informed Neural Network (PINN) architectures, the project aims to produce fast, reliable, and uncertainty-aware surrogate models for shielding design, dose assessment, and regulatory decision-support.

Job Description & Key Responsibilities

The appointed researcher will be expected to undertake the following duties:

• Develop and validate detailed MCNP and/or GEANT4 radiation transport models.
• Generate high-fidelity benchmark datasets for diverse radiation shielding and dose-assessment scenarios.
• Formulate and train AI and PINN surrogate models utilizing modern machine-learning frameworks.
• Implement uncertainty quantification (UQ) and rigorous validation methodologies.
• Benchmark surrogate models against analytical formulas and Monte Carlo reference solutions.
• Assist in building prototype computational tools and software pipelines for regulatory applications.
• Author high-impact scientific publications, technical reports, and deliver presentations at academic conferences.
• Assist in guiding and mentoring undergraduate and graduate students participating in the project.

Eligibility and Qualifications

Candidates must fulfill the following educational and technical requirements:

• Education: A PhD (for the Postdoctoral Fellow role) or a BSc/MSc (for the Research Assistant role) in Nuclear Engineering, Computational Physics, Radiation Physics, Medical Physics, Scientific Computing, Applied Mathematics, Computer Science, or a closely aligned discipline.
• Core Knowledge: Strong theoretical and practical foundation in radiation transport and computational physics.
• Simulation Experience: Demonstrated proficiency with Monte Carlo codes such as MCNP or GEANT4.
• Programming Skills: Solid programming proficiency in Python, C/C++, MATLAB, or related scientific computing languages.
• Research Capability: Proven ability to conduct independent research, solve complex technical problems, and produce peer-reviewed scientific publications.

Preferred Qualifications

Preference will be extended to applicants with hands-on expertise in one or more of the following domains:

• Physics-Informed Neural Networks (PINNs) and scientific machine learning.
• Deep learning frameworks (PyTorch or TensorFlow).
• High-Performance Computing (HPC) workflows and parallelization.
• Radiation shielding analysis, dosimetry, and radiological protection.
• Uncertainty quantification methods in scientific modeling.

Required Application Documents

Interested candidates should prepare the following documents before submitting their application:

• A detailed Cover Letter outlining research experience, technical skills, and alignment with the project.
• An up-to-date Curriculum Vitae (CV).
• A full list of scientific publications and relevant conference contributions.
• Contact details (names, affiliations, and professional email addresses) of three academic or professional references.

How to Apply

Applications must be submitted electronically through the official UAEU recruitment portal. Please ensure all required documents are uploaded in PDF format prior to the closing date.

Click Here to Apply Online at UAEU Portal

Last Date for Application

The closing date for receiving applications is November 30, 2026. Early submission is strongly encouraged as applications may be reviewed on a rolling basis.