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Field
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. This position offers substantial resources, including access to the SeaWulf computing cluster and cutting-edge GPU clusters housed at IACS and CEWIT. The Empire Innovation Professor will join a robust community
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familiarity with Deep Learning, including PyTorch would convey a significant advantage. They will have access to our in-house GPU-enabled High Performance Computing platform as well as national HPC resources
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provided with the working material (working station, PC and access to local GPU clusters) as well as with a discounted rate for the close-by Inria canteen, together with a gross salary of 2650 euros/month
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documentation, and promote the benefits of our HPC resources across the institution. Collaborating closely with academic staff, researchers, and IT Services, you will ensure the HPC and GPU facilities
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. Experience with algorithm design, embedded DSP development, multithreaded programming, GPU development, SDR hardware platforms, FPGA development, and/or Linux-based designed tools is desired. Representative
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/GPU architectures and even quantum computing are currently actively explored. Candidates are sought that align with these research areas. A broad interest in teaching topics would additionally be
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structured and unstructured datasets, and GPU-accelerated computing. Proven experience with Large Language Models. Required Skill/Ability 3: Sound background in theoretical and applied machine learning/deep
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inference Develop distributed model training and inference architectures leveraging GPU-based compute resources Implement server-less and containerized solutions using Docker, Kubernetes, and cloud-native
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development (e.g., PyQt, Tkinter) CUDA for GPU acceleration Scientific computing libraries such as NumPy and SciPy A keen interest in scientific computing, atmospheric sciences, or advanced instrumentation is
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quantitative genetics, machine learning, bioinformatics, and population genetics, and their applications in an agricultural setting A modern dedicated computational infrastructure (CPUs & GPUs) Well-developed in