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FPGAs, CGRAs, and many Machine Learning accelerators, offer significant opportunities for improving performance and energy efficiency compared to traditional CPUs/GPUs. Yet, porting and optimizing code
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optimization; and experience supporting end-users in technical research environments. PREFERRED: Familiarity with GPU computing; scripting in Python or Bash; and container orchestration tools like Docker and
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Work location Zürich or Lugano Topic B: Simultaneous tree traversal with Producer-Consumer pattern on GPUs Abstract Simultaneous tree traversal, also referred to as dual tree traversal, can be applied
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compressible gas dynamics, heat transfer, free-surface/melt behaviour, and mass transfer driven by phase change, within a GPU-accelerated solver to reduce simulation turnaround times. You will develop and
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compressible gas dynamics, heat transfer, free-surface/melt behaviour, and mass transfer driven by phase change, within a GPU-accelerated solver to reduce simulation turnaround times. You will develop and
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directly with internal and external stakeholders to resolve issues and drive operational improvements. PREFERRED: Familiarity with IT service management frameworks, vendor coordination, and GPU or cloud
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supporting end-users in technical research environments. PREFERRED: Familiarity with GPU computing; scripting in Python or Bash; and container orchestration tools like Docker and Kubernetes; and experience in
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minimum of ten years of experience in high-performance computing, including five or more in a leadership capacity managing large-scale GPU-based systems; a strong technical background in HPC infrastructure
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coordination, and GPU or cloud-based infrastructure. 12/3/2025
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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