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the area of the AI Computer Systems. The successful candidate will lead an innovative research program in cutting-edge AI computer system technologies. The position requires knowledge of both hardware and
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. Describe a deep learning project you have executed. Projects in computer vision for microscopy image analysis are especially relevant. Include a link to a code repository if possible. If you contributed to a
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contributions, and addressing bugs that arise as the platform is used in active research settings. The platform is built in C++ with CUDA-based computation running on NVIDIA GPUs, and is being developed both
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variety of computational devices (e.g. CPUs and GPUs) while ensuring overall consistency and performance. - contribute to identify new CSE applications domains, such as condensed matter systems, quantum
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with edge computing or embedded systems (e.g., NVIDIA Jetson, Raspberry Pi) Background in real-time processing and GPU acceleration (CUDA) Participation in relevant competitions (e.g., Kaggle, computer
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NEST: https://nest-simulator.readthedocs.io Your tasks in detail: Work with the NEST main code base and experimental branches Dissect the spiking network simulation cycle into phases and capture the flow
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them. Research Computing & AI Enablement - Work with the Architecture team to build scalable HPC and GPU-enabled environments on IaaS cloud sites along with other specialized hosted solutions. Work
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Information Benefits Trabajo en IA generativa de vanguardia aplicada al habla / Work on cutting-edge generative AI for speech Acceso a servidores GPU y recursos de cómputo / Access to GPU servers and computing
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., Bayesian, hierarchical, time-series), experience with sensor-based data (such as eye tracking, EEG, and heart rate), and proficiency in computational workflows, including distributed and GPU-based systems
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, forward-looking, and varied research fields and projects, with numerous development opportunities Modern hardware and infrastructure at the workplace, from compute and GPU servers to supercomputers