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strategies for large-scale or streaming data. Develop parallelized and GPU-accelerated learning modules, ensuring scalability and performance efficiency. Build and maintain robust data pipelines for high
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). Experience with shared and distributed memory parallel programming models such as OpenMP and MPI. Experience with one more GPU or performance portability programming language (e.g., CUDA, HIP, Kokkos, SYCL
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- 21:59 (UTC) Country Netherlands Type of Contract Temporary Job Status Not Applicable Hours Per Week 36.0 Is the job funded through the EU Research Framework Programme? Not funded by a EU programme Is
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340,000. Located in the global city of Miami, the university offers more than 200 degree programs at the undergraduate, graduate and professional levels, including medicine and law. FIU faculty are leaders
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. Preferred Qualifications : * Experience in programming on modern computing platforms including x86 and ARM-based CPUs and accelerators such as NVIDIA or AMD GPUs. * Experience working in an academic research
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theory to translate into real-world AI applications across science, business, and society. Our academic strength is validated by seven disciplines in the global top 1% (ESI) and a Data Science program
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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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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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) ● Experience working in Linux-based high-performance computing environments. ● Experience with parallel programming models, such as MPI, OpenMP, CUDA, or related technologies. ● Experience compiling
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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