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well as large-scale GPU computing facilities for deep learning. Our Lab aims to hire a Research Fellow to lead a research project on Real-World Deepfake Detection and Image Forgery Localization. The role will
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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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systems, and the Zero-G Lab, a unique facility designed to emulate proximity operations under space-like conditions. In addition, CVI2 provides high-performance GPU computing resources that support the
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provides high-performance GPU computing resources that support the design and training of advanced AI models. The research agenda of CVI2 focuses on cutting-edge topics such as 3D understanding and
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or streaming data. Develop parallelized and GPU-accelerated learning modules, ensuring scalability and performance efficiency. Build and maintain robust data pipelines for high-throughput modeling over
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We are seeking a highly motivated PhD student to perform fundamental research and to conceive truly sparse solutions (on both, CPU and GPU) for dynamic sparse training, aiming to cut the training
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growing GPU cluster containing thousands of high-end GPUs. Depending on the day, we might be diving deep into market data, tuning hyperparameters, debugging distributed training performance, or studying how
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collaborative, international team. We offer Cutting-Edge Resources: Access to state-of-the-art compute and GPU infrastructure, including H100 and B300 GPU clusters. Innovation: The opportunity
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in GPU programming one or more parallel computing models, including SYCL, CUDA, HIP, or OpenMP Experience with scientific computing and software development on HPC systems Ability to conduct
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). Practical experience with cloud computing platforms (e.g., AWS, GCP, Azure). Additional Qualifications Experience with multi-GPU model training and large-scale inference. Familiarity with modern AI