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, networks and GPU resources. The role ensures secure, efficient, and scalable systems to support research and administrative functions. This position work closely with PI, researchers and technical vendors
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dynamic and enterprising individual to join us as a Senior HPC Application Engineer. Key Responsibilities Port scientific applications to GPU (e.g., using CUDA, HIP, OpenACC) or optimize for multi-core CPUs
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these codes in C++ or Fortran Adopting these codes for multiple-CPU and/or GPU platforms via parallelization schemes. Validating these codes via canonical and real-world examples. Job Requirements: PhD in
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when necessary. Work closely with ODFM to facilitate request for office and lab access. Manage any IT matters, including IT equipment allocation and support for GPU servers (if required). 2. Support on
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performance with energy consumption reduction. Key Responsibilities: Conduct research on energy-efficient computing systems, including CPU/GPU/accelerator architectures, virtualization, and workload scheduling
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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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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
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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