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project management skills, and the ability to prioritise work, work to deadlines and undertake multiple parallel projects Demonstrated ability to identify, assess, test and evaluate technical applications
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include high-performance computing, middleware and computing systems. Recent relevant research experience to include: Undertaking research in the area of high-performance / distributed / parallel computing
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optimize large-scale distributed training frameworks (e.g., data parallelism, tensor parallelism, pipeline parallelism). Develop high-performance inference engines, improving latency, throughput, and memory
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of custom computer code, and the processing of large-scale simulations using massively parallel resources such as NERSC and Raj cluster at Marquette. Conduct research with a significant degree of independence
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laboratory and database administration. Experience with processing data from massively parallel DNA sequencers, computation on high performance compute clusters, using open source database management systems
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invasive sensing tools to monitor metabolites, oxygen, carbon dioxide, pH, and other parameters. Ideally, the methods can function in parallel and on a large scale. The research is vital to understand key
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). Preferred Qualifications: Familiarity with advanced storage solutions and parallel file systems (e.g., Lustre, GPFS, or BeeGFS). Advanced knowledge of Linux operating systems, networked storage environments
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skills in a retail environment that parallels the functions of this position. Background Investigation Statement: Prior to hiring, the final candidate(s) must successfully pass a pre-employment background
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Identify new applications for Machine Learning in science, engineering, and technology Develop, implement and refine ML techniques Implement parallel ML training on the High Performance Computers Engage in
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chemistry, with experience planning and troubleshooting synthetic routes and performing parallel library synthesis. The ideal candidate should have experiences with one or more of the following: working with