Research Fellow (Ocean / Hydrological modelling)

Interested applicants are invited to apply directly at the NUS Career Portal. Please note your application will only be processed if you apply via NUS Career Portal.

NUS Career Portal link: https://careers.nus.edu.sg/job/Research-Fellow-%28Ocean-Hydrological-modelling%29/32304-en_GB/

We regret that only shortlisted candidates will be notified.

Job Description

The Singapore Nuclear Research and Safety Institute (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 Associate/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 project:

• Hydrological/ocean modelling

Various processes of radionuclides in water bodies within and around Singapore will be modelled, including hydrodynamics, dispersion, and food-chain transfer etc. This work aims to improve the understanding of radionuclide transport and dispersion mechanisms in aquatic environment, providing a foundation for subsequent radiological impact and consequence assessments in the context of Southeast Asia.

Qualifications

• A postgraduate degree in a relevant discipline, such as oceanography, hydrology, environmental science, biology, or related field.
• Proficiency in programming with languages such as Fortran, C/C++, Python, and MATLAB familiarity with Linux operating system and high-performance computing environments.
• Experience with ocean and hydrological models, such as Deflt3D, ROMS, NEMO, or HYCOM is strongly preferred.