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interactive computing, and security and distributed systems. Work description This is a permanent, full-time position as senior lecturer in computer science with a focus on computer systems engineering. The
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interactive computing, and security and distributed systems. Work description The position involves teaching at bachelor's and master's level in computer science, with a focus on practical components such as
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MOHAMED BIN ZAYED UNIVERSITY OF ARTIFICIAL INTELLIGENCE | Dhabi Kalan, Haryana | India | about 2 months ago
experts in computational microscopy and machine learning systems, blending expertise in advanced bioimage informatics and parallel computing: Dr. Min Xu – Affiliated Associate Professor of Computer
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-scale artificial intelligence. You will work at the forefront of technology with access to the latest generation of GPU accelerators, high-speed interconnects, parallel file systems and distributed AI
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Inria, the French national research institute for the digital sciences | Talence, Aquitaine | France | 12 days ago
core of the project is the exploration of leveraging task-based parallel and distributed programming techniques in the DDF-pipeline software components with the aim to accelerate such processing on high
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Inria, the French national research institute for the digital sciences | Villeneuve, Queensland | Australia | 12 days ago
, computational intelligence, heuristic search, or related areas, as well as to candidates with expertise in parallel and HPC computing combined with a solid understanding of combinatorial optimization. While
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across Linux environments, programming and scripting languages, job scheduling, scientific applications, optimized compilers, mathematical libraries and algorithms, and distributed and parallel file
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systems and servers. Documenting system administration procedures for routine and complex tasks. Technical Environment: Linux build automation in a large, distributed computing environment with Puppet
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benchmarking of parallel and distributed computing systems and of the workflow systems that run on them. Familiarity with the FAIR data and research software principles, and with producing AI-ready
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pipelines for reproducible, efficient and scalable training and inference on parallel, distributed and GPU-accelerated computing systems Benchmark the developed approaches against established methods