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community. We provide the resources to match your ambition: Industrial-Scale Computing: Exclusive access to massive GPU clusters and high-performance computing. Guaranteed Talent Pipeline: Generous
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infrastructure, model training, and inference systems. You'll design, develop, and optimize scalable data pipelines and build multi-node GPU training and inference pipelines for foundational models. You'll also
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adaptive optimization during needle insertion, integrating live ultrasound imaging with GPU-accelerated dose calculation and optimization. The Postdoctoral Research Associate will join a multidisciplinary
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Python, with experience in modern software development environments (Linux, Docker, Cloud Service Deployment). Desired: Experience with High-Performance Computing or GPU programming (CUDA). Specialized
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-based CPUs and accelerators such as NVIDIA or AMD GPUs. ● Experience working in an academic research computing center or large-scale HPC environment. ● Experience with GPU computing and
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highly-motivated candidate, skilled in numerical model development (programming in FORTRAN, numerical methods, HPC environment). Experience in numerical methods on unstructured grids and/or GPU would be
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frameworks). Experience using open-source model ecosystems such as Hugging Face (Transformers, Datasets, Accelerate). Experience using or supporting supercomputing or GPU-enabled clusters. Experience with data
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scalability of simulation workflows via: Parallelization and performance engineering GPU/accelerator optimization Algorithmic innovation Experience applying machine learning or AI to molecular simulation
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. Duties: Develop and execute a strategic roadmap for research computing infrastructure, including GPU-enabled high-performance computing (HPC) environments and enterprise storage systems including
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academic setting Proficient in at least two programming languages used in research (e.g. Python, C++, Fortran) Experience with programming paradigms used in HPC (e.g., MPI, GPU-programming) Experience