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TensorFlow, PyTorch, etc.) Experience with GPU computing, especially for AI/ML calculations Understanding of multi-user computing systems, environments and networks Experience with teaching and/or tutoring in
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transformations at such interfaces, and how they are influenced by external electric fields and electrolyte composition. Access to high performance computing facilities including GPU clusters will be provided
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and classical computer vision; Develop quantitative features, including color metrics (RGB/HSV/Lab), texture (GLCM, LBP), geometry, and other visual proxies for clinical assessment; and Build image
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the College of Engineering. UNLV GPU Cluster (named RebelX) is also available for A.I. research and education. Detailed information about the CEEC Department can be found at: http://www.unlv.edu/ceec MINIMUM
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performance computing systems or cloud infrastructure (including GPU-accelerated workloads). Practical experience with modern deep learning frameworks, model serving in production, and building end-to-end data
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development skills Model deployment (e.g., ONNX, TensorRT) Edge computing or embedded vision systems (e.g., NVIDIA Jetson Nano) Real-time processing and GPU acceleration Experience working on industry R&D
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are passionate about what they do. Join us and be a part of the diverse Caltech community. Job Summary The Research Assistant in Scientific Computing will work at the AI+Science Lab led by Prof. Anima Anandkumar
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the Computer Science program at New York University Abu Dhabi, seeks to recruit a research assistant to work on the intersection of compilers and deep learning. Many companies, such as Google, Facebook, and Amazon
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Germany Application Deadline 2 Nov 2025 - 22:59 (UTC) Type of Contract To be defined Job Status Other Offer Starting Date 17 Oct 2025 Is the job funded through the EU Research Framework Programme? Not
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quality, diversity, and biological relevance using standard metrics and expert review. Anonymised digital images from tissues in biobanks will be used to train generative models on university computing