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-up funding, commensurate with rank and the proposed research programme Access to secure clinical and multi-omics data environments Modern GPU, and high-performance computing resources, plus dedicated
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numerical solvers for 2D and 3D phase field models Develop HPC-ready simulation pipelines for large-scale rupture and fracture-fluid systems Optimize performance for modern architectures including GPUs and
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development skills Model deployment (e.g., ONNX, TensorRT) Edge computing or embedded vision systems (e.g., NVIDIA Jetson Nano) Real-time processing and GPU acceleration Experience working on industry R&D
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for early detection, differential diagnosis, progression monitoring, and treatment design. Key attractions are access to a high-performance computing cluster, NUS HPC (H100/H200 GPU clusters), two 3T Prisma
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of this role is to oversee the construction and management of a High-Performance Computing (HPC) cluster comprising 4,500 CPU/GPU cores, BeeGFS storage, and Infiniband interconnects. The ideal candidate will
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with physical-based and machine learning methods in atmospheric science. Proficiency in Linux-based high-performance computing systems, GPU-based programming and prevailing AI tools. Experience in urban
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for multiple-CPU and/or GPU platforms via parallelization schemes. Validating these codes via canonical and real-world examples. Job Requirements: PhD in Electrical and Electronic Engineering, Applied