Postdoctoral Fellow
Indexed description
- Develop and validate MCNP and/or GEANT4 radiation transport models.
- Generate benchmark datasets for shielding and dose-assessment scenarios.
- Develop AI and PINN surrogate models using modern machine-learning frameworks.
- Implement uncertainty quantification and validation methodologies.
- Participate in model benchmarking against analytical and Monte Carlo reference solutions.
- Assist in the development of prototype computational tools for regulatory applications.
- Contribute to scientific publications, reports, and presentations.
- Participate in mentoring graduate and undergraduate students involved in the project.
- BSc/MSc (a PhD for postdoctoral) in Nuclear Engineering, Computational Physics, Radiation Physics, Medical Physics, Scientific Computing, Applied Mathematics, Computer Science, or a closely related field.
- Strong background in radiation transport and/or computational physics.
- Experience with Monte Carlo simulation tools such as MCNP or GEANT4.
- Programming experience in Python, C/C++, MATLAB, or related scientific programming languages.
- Strong analytical and problem-solving skills.
- Demonstrated ability to conduct independent research and publish scientific work.
- Physics-Informed Neural Networks (PINNs)
- Machine learning and deep learning
- PyTorch or TensorFlow
- High-performance computing (HPC)
- Radiation shielding and dosimetry
- Uncertainty quantification
Cover letter describing research experience and interests. Curriculum vitae (CV). List of publications. Contact information for three references
Salary Range
8000-12000 AED/month
Close Date Kindly apply before the closing date.
30/11/2026
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