The candidate will provide technical leadership, help shape research directions, and mentor teams across multiple efforts involving hardware-software co-optimisation, efficient AI model training and inference, and heterogeneous deployment. The role will also involve engaging with academic collaborators, HPC providers, chip and cloud vendors, and industry partners across strategic sectors.
Strategic Research Areas
HPC Capability Development
Singapore’s HPC roadmap focuses on building core HPC capabilities, including hardware-software co-design, profiling and tuning for performance and energy efficiency, and AI-enabled adaptive code development for emerging HPC architectures. This focus area ensures that Singapore’s HPC infrastructure can evolve rapidly with next-generation processors, accelerators, and memory technologies.
HPC-Enabled Efficient AI Models
With the rapid scaling of AI workloads, optimising large-scale AI models and foundation models is a national priority. This focus area addresses distributed training frameworks, data movement and storage efficiency, and co-optimisation of computation across GPUs, CPUs, and specialised accelerators. These efforts enable sustainable, large-scale AI research and deployment in Singapore.
HPC-Enabled Efficient Deployment
The growing complexity of data centres and hybrid cloud environments requires efficient workload scheduling, orchestration, and heterogeneous deployment. This focus area develops AI-driven resource allocation and multi-agent scheduling strategies, enabling seamless integration across supercomputers, edge clusters, and cloud platforms. It directly supports national priorities in sustainability, advanced manufacturing, and healthcare.
Description of Responsibilities
Provide technical leadership across HPC capability development, AI model optimisation, and deployment efficiency focus areas.
Shape the research and development roadmap for HPC-AI integration, with a focus on scalability, sustainability, and translational outcomes.
Engage and collaborate with ecosystem stakeholders, including NSCC, global HPC centres, chip vendors, cloud providers, and industry partners, to ensure alignment with national priorities and foster strategic collaborations.
Mentor and grow Singapore’s HPC-AI talent pipeline, including researchers, engineers, and postdoctoral fellows.
Lead or co-lead research projects and industry engagements where deep technical expertise is critical.
Drive high-quality publications, open-source contributions, and where appropriate, protect intellectual property through patents.
Represent Singapore’s HPC initiatives at international forums and strengthen global visibility for the ecosystem.
Key Technical Areas
Hardware-Software Co-optimisation: GPU/CPU/FPGA tuning, chip-specific profiling, compiler optimisation.
AI Model Efficiency: Foundation/LLM optimisation, distributed training, scalable inference, data movement strategies.
Deployment Scalability: Resource scheduling, workload orchestration, heterogeneous HPC environments, multi-agent coordination.
Energy Efficiency: Sustainable computing architectures, power-aware resource allocation, carbon-aware scheduling.
Required Qualifications
PhD in Computer Science, Computational Science, or related field (or equivalent industry experience).
Deep expertise in HPC systems, including GPU clusters, parallel/distributed computing, and heterogeneous architectures.
Proven track record in optimising large-scale computational workloads and/or AI model deployment.
Strong programming skills in C/C++, Python, CUDA, and familiarity with HPC frameworks (MPI, OpenMP).
Experience with AI/ML frameworks (e.g. PyTorch, TensorFlow) and their integration with HPC systems.
Demonstrated leadership of technical teams and complex, multi-stakeholder projects.
Excellent communication skills for engaging with researchers, industry, and government stakeholders.
Preferred Qualifications
Knowledge of domain-specific applications in sustainability, manufacturing, or healthcare.
Track record of successful industry collaborations, technology transfer, and translational impact.
Experience with cloud-based HPC and hybrid computing environments.
Familiarity with quantum-classical hybrid computing concepts and future integration paths.
The above eligibility criteria are not exhaustive. A*STAR may include additional selection criteria based on its prevailing recruitment policies. These policies may be amended from time to time without notice. We regret that only shortlisted candidates will be notified.
Type of Employment : Full-Time
Work Location : Fusionopoli

Please refer the Job description for details