Job Description

The Singapore Nuclear Research and Safety Initiative (SNRSI), a university-level research institute at NUS established in 2014, is committed to excellence in nuclear safety research. Within SNRSI, the Radionuclide Dispersion and Dose Assessment team specialises in modelling the migration and impact of radioactive pollutants through various pathways in Singapore and the surrounding region. The team is dedicated to advancing the academic community while tackling real-world challenges faced by government agencies and stakeholders.

With several positions open for Research Assistant/Research Associate, we welcome motivated candidates to join us – an excellent opportunity to collaborate with colleagues from world-leading universities and develop essential skills in the exciting world of modelling and cutting-edge technologies, including data analysis and visualisation, machine learning, computational methods, and more. If offered the position, you will participate in the following projects, based on your background and strengths.

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• Radionuclide dispersion modelling

The migration of radionuclides, in the air or water bodies (both surface and underground) will be modelled using either community dispersion models or in-house-developed codes. The aim is to enhance our understanding of how radionuclides are transported and dispersed in the environment, providing a robust foundation for further impact or consequence assessment.

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• Radiological impact and dose assessment

Mathematical models or empirical approaches are employed or developed to quantitatively analyse radionuclide pathways. The radiation exposure doses, potential contamination of food or water sources are subsequently estimated. The goal is to provide reliable and practical references for emergency planning or mitigation measure implementation.

Qualifications

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• A degree or higher qualification in a relevant field, such as physics, mathematics, environmental sciences, and computer science, etc.
• A strong understanding of fundamental physics, mathematics, and statistics.
• Proficient in Python programming. Having experience in other coding languages, such as C/C++, Fortran, MATLAB, or Linux shell scripting, is a plus.
• Experience with modelling using tools/models such as FLUENT/OpenFOAM, Deflt3D, ROMS, WRF, HYSPLIT, or RODOS is considered an advantage.

More Information

Location: Kent Ridge Campus

Organization: S'pore Nuclear Rsch & Safety Initiative