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Field
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members Sriram Pemmaraju and Sourya Roy on sampling problems in the distributed and parallel computing setting. The ideal candidate will have research experience in sampling algorithms and related areas
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scalable training and inference on parallel, distributed and GPU-accelerated computing systems Benchmark the developed approaches against established methods, assessing predictive performance, generalisation
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practical knowledge of machine learning with large datasets Experience : Experience with cloud-based, parallel, or distributed computing environments Hands-on experience developing or deploying production ML
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practical knowledge of machine learning with large datasets Experience : Experience with cloud-based, parallel, or distributed computing environments Hands-on experience developing or deploying production ML
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knowledge of machine learning with large datasets Experience : Experience with cloud-based, parallel, or distributed computing environments Hands-on experience developing or deploying production ML/AI systems
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knowledge of machine learning with large datasets Experience : Experience with cloud-based, parallel, or distributed computing environments Hands-on experience developing or deploying production ML/AI systems
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community and the general public in the Denver metropolitan area. The current strengths of the faculty are in the areas of algorithms, artificial intelligence, computer networks, graphics, parallel and
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Professor of Machine Learning and Computer Science, MBZUAI. Dr. Ho specializes in distributed machine learning and systems architecture. His expertise drives the design of robust, parallelized systems
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foundation models, directly advancing the frontier of computational biology and machine learning. You will also implement parallel systems capable of training such models across large GPU clusters on cryoSTEM
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-time Hours Per Week 37h15 Offer Starting Date 26 Oct 2026 Is the job funded through the EU Research Framework Programme? Not funded by a EU programme Is the Job related to staff position within a