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of relevant experience in Linux systems administration or HPC systems engineering. Preferred Qualifications Demonstrated experience leading the design and deployment of HPC or large-scale distributed computing
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algorithms * Parallel algorithms and distributed computing * Parameterized complexity and structural graph theory * Random structures and randomized algorithms * Sublinear and streaming algorithms
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. You have experience in matrix algorithms, data compression, parallel computing, optimization of advanced applications on parallel and distributed systems. An excellent scientific track record proven
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for scientific computing to support users in the process of solving increasingly complex compute- and data-intensive problems in science and engineering on high-end parallel and distributed computing platforms
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focus often neglects other dimensions of processes, such as the time between activities and the time required for specific steps, the spatial distribution of tasks across locations, or the intricate
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The University of North Carolina at Chapel Hill | Chapel Hill, North Carolina | United States | 21 days ago
and Experience: Distributed parallel training and parameter-efficient tuning. Familiarity with multi-modal foundation models, HITL techniques, and prompt engineering. Experience with LLM fine-tuning
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signal processing and/or survey datasets. ML & AI techniques and applications. HPC and orchestration of scientific data processing workflows. Parallel computing (GPU & CPU). good software engineering
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between nonlinear dynamics and computing metrics in micro-ring resonators and coupled ring-resonator architectures Evaluate the number and spatial distribution of coupled cavities for photonic reservoir
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100%, Zurich, fixed-term We have an open PhD position at the intersection of machine learning, embedded intelligence and human–computer interaction. The project will explore how learning systems can
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circuits for enhancing computing efficiency through parallelism. The PhD student will participate in an international team in an EU-funded Doctoral Network project called MINDnet. The project consists of 15