Research Fellow – AI-Driven CFD & Foundation Models

National University of Singapore; Singapore; On-site; SGD 60,000 - 100,000; Full time

Job summary

The National University of Singapore seeks a researcher to develop deep-learning frameworks and foundational models to study transport phenomena across multiple spatial and temporal scales. The candidate will contribute to cutting-edge CFD research with emphasis on data-driven approaches and advanced numerical methods.

Qualifications include substantial CFD research experience, strong C++ programming skills, and a PhD in a related field.

Qualifications

• Substantial research experience in computational fluid dynamics.
• Expertise in flow stability analysis, data-driven modelling, or flow control.
• Strong programming and numerical solver development skills (C++, MPI/OpenMP, GPU-accelerated simulations).
• A Ph.D. degree in hydraulic engineering, fluid mechanics, mechanical engineering, applied mathematics, or a related discipline.

Responsibilities

• Develop deep-learning frameworks and foundation models for transport phenomena across a wide range of spatial and temporal scales.

Skills

Flow stability analysis

Data-driven modelling

Flow control

Education

PhD in hydraulic engineering / fluid mechanics / related field

Tools

C++

MPI/OpenMP

GPU-accelerated simulations

Job description

The National University of Singapore seeks a researcher to develop deep-learning frameworks and foundational models to study transport phenomena across multiple spatial and temporal scales. The candidate will contribute to cutting-edge CFD research with emphasis on data-driven approaches and advanced numerical methods.

Qualifications include substantial CFD research experience, strong C++ programming skills, and a PhD in a related field.