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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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the following areas is preferred, and an exceptionally strong candidate in a single area is also encouraged to apply. Relevant areas include: Parallel and distributed graph and or ML algorithms
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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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Systems and contribute research in areas such as distributed systems, cloud and edge computing, high-performance and parallel computing, large-scale data processing, resource management and scheduling
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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
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Computer Science, a Bachelor of Science degree in Cybersecurity, a Master of Science degree in Computer Science, and two multidisciplinary PhD degrees in Computer Science and Information Systems and Engineering and
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development skills; distributed or parallel computing is a plus. Experience designing and executing field experiments in urban or environmental settings, with willingness to engage in fieldwork in dense urban
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conduct world-class applied research. We change and make a difference. Do you want to become one of us? Work description The PhD positions are part of the research portfolio within Mechanical Engineering