Jobs in Singapore, straight from employers.

HPC Domain Specialist (Climate/Weather)

On-site in Singapore·Added yesterday (last checked 22 Oct)

A*STAR

643 open roles

Apply

Overview

Work mode: On-site, Singapore
Experience: 3+ years

Skills

The role

ABOUT THE ROLE

Singapore's top climate and weather experts are tackling one of the most critical challenges of our time. As our Climate Domain Specialist, you will be their essential partner, the computational expert who empowers them to harness the massive power of the new supercomputer for their vital modelling.

Your work is the critical link that translates their scientific goals into high-performance simulations, enabling the high-resolution modelling essential for our national climate resilience strategy. You will bring expertise in large-scale numerical simulation and high-performance computing, with experience in climate/weather, AI-driven modelling, Computational Fluid Dynamics (CFD), or related computational science domains.

This is a rare opportunity to be the go-to HPC specialist for the nation's climate research community, making a direct and lasting impact by scaling their work to new frontiers. Candidates from CFD and adjacent computational engineering domains who are keen to apply their expertise to climate and weather applications are also encouraged to apply.

RESPONSIBILITIES

Provide HPC and scientific domain advice to users of NSCC systems.
Engage and collaborate with new researchers, communities, and disciplines with computationally intensive requirements.
Support and optimise large-scale scientific and numerical simulation workloads.
Work with HPC performance engineers to profile and build performance models of scientific applications and workflows.
Design, develop and implement HPC software best practices for large-scale scientific applications and workflows.
Assist in the planning and design of future HPC systems, including benchmarking relevant scientific and computational workloads on various platforms and recommending the most suitable architecture for the research community.
Develop HPC utilities and automated testing tools for NSCC HPC systems.
Develop HPC user and best practice guides for NSCC HPC systems.
Keep up to date with developments in relevant scientific computing domains, as well as HPC systems and software technologies.

QUALIFICATIONS

Master's degree in engineering, computer science, computational science, atmospheric science, applied mathematics, or another relevant field.
Ideally, 3 years of experience in climate/weather simulation, CFD, AI-driven weather modelling, or other large-scale numerical simulation workloads.
Experience in building scientific modelling and simulation applications from source code.
Good knowledge of scientific application performance optimisation, profiling and troubleshooting, particularly for computationally intensive workloads.
Familiarity with commonly used applications and frameworks in climate/weather, AI-driven weather modelling and/or CFD would be advantageous. Relevant applications include:
- Climate/Weather: ICON, LFRic, MPAS, NEMO, WRF
- AI Climate/Weather: FourCastNet, AIFS, Anemoi, Earth-2, StormCast, GraphCast, Pangu-Weather
- CFD: OpenFOAM, Neko, SU2
Familiar with HPC development tool chains and scientific application software stacks relevant to computational modelling and simulation.
Familiar with Linux, scripting languages, HPC profiler and debugger tools.
Familiar with HPC job schedulers, OpenMP & MPI, and container technologies.
Familiar with HPC storage e.g. GPFS and Lustre.
Programming skills in C/C++, Python, or Fortran are highly desired.
Demonstrated team player with strong problem-solving skills.
Demonstrated effective communication skills, including the ability to articulate technical concepts to a diverse range of audiences.
Demonstrated ability and willingness to contribute novel ideas and approaches in support of the research community.
Demonstrated passion for continuous learning and exploring new technologies or domains, including the ability to apply computational expertise across different scientific domains.