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Field
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Workflows: Collaborate with computational scientists to optimize parallel computing workflows and port research tools to high-end computing platforms. Automate Developer Workflows: Design tools and frameworks
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welcome applications from all areas of computer science, we especially encourage candidates with expertise in: Software Engineering Cybersecurity Artificial Intelligence and related domains Parallel and
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PhD degree in Computer Science, Physics or a related field Experience with parallel programming models Strong programming skills in C/C++ and/or Python Knowledge of distributed memory programming with
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simulation, AI based detector design optimization, streaming computing model development, production, distributed computing and workflow management, software infrastructure, particle ID, tracking
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media, news media, digital signage, podcast, signature events, and executive presentations. This candidate must be comfortable managing multiple projects in parallel, many of which require the execution
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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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exploring them. Basic data preprocessing, feature engineering, and model evaluation, or a strong willingness to gain hands-on experience. Eagerness to learn HPC concepts, including parallel computing
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clusters, including CPU and GPU architectures; Proficiency with job schedulers (e.g., Slurm); Knowledge of parallel and distributed computing principles; Understanding of data security and compliance
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parallel and distributed software applications. Identify, create, and disseminate basic and advanced student workflows. 6. Provide end-user computer support for high-end computing, labs, robotics lab, 3D
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) for a given Tiramisu program, many code optimizations should be applied. Optimizations include vectorization (using hardware vector instructions), parallelization (running loop iterations in parallel