Research Fellow (Physics / Environmental Science / Computer Science)

National University of Singapore; Singapore; On-site; SGD 60,000 - 80,000; Full time

Job summary

A leading educational institution in Singapore is seeking motivated candidates for the position of Research Fellow within its Nuclear Research and Safety Initiative. Candidates must hold a PhD in a relevant field and possess strong programming skills in Python. The role involves modelling radionuclide dispersion and assessing radiological impacts, providing essential insights for environmental safety and emergency planning. This position offers a unique opportunity to work with collaborative, world-class researchers and develop critical skills in an impactful field.

Qualifications

• Strong understanding of fundamental physics, mathematics, and statistics.
• Experience with coding languages such as C/C++, Fortran, MATLAB, or Linux shell scripting is a plus.
• Experience with modelling tools/models is considered an advantage.

Responsibilities

• Model radionuclide dispersion in air or water bodies.
• Quantitatively analyse radionuclide pathways for radiation exposure dosage.
• Provide references for emergency planning and mitigation measures.

Skills

Proficient in Python programming

Fundamental physics understanding

Mathematics expertise

Statistics knowledge

Education

PhD in relevant field such as physics, mathematics, environmental sciences, or computer science

Tools

FLUENT/OpenFOAM

Delft3D

ROMS

WRF

HYSPLIT

RODOS

Job description

Company description

The National University of Singapore is the national research university of Singapore. Founded in 1905 as the Straits Settlements and the Federated Malay States Government Medical School, NUS is the oldest higher education institution in Singapore

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 Fellow, 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.

• 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.

• 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

• A PhD 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 Institute