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‑space exploration, and on‑line operational optimization of power systems. Your tasks in detail: Become familiar with our previously developed neural network superstructure for learning iterative
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detection with minimal latency. Combined with efficient signal processing, this approach enhances detection accuracy while optimizing resource use, supporting cybersecurity and sustainability in IIoT networks
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to accelerate solving AC power flow (AC-PF) computations, potentially facilitating real‑time contingency analysis, rapid design‑space exploration, and on‑line operational optimization of power systems
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prediction Integration of domain decomposition methods into the learning framework to enable efficient model parallel training Implementation and optimization of GPU-accelerated training pipelines Validation
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bacteria; • Application and optimization of molecular methods for bacterial detection and identification (PCR, qPCR, LAMP); • Support in evaluating and validating rapid diagnostic platforms in the lab and
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efficient model parallel training Implementation and optimization of GPU-accelerated training pipelines Validation of models on patient-specific geometries obtained from MRI data Participation in conferences
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Job Description The Vlaisavljevich Lab (https://ultrasound-lab.beam.vt.edu) is looking for a part-time research assistant to explore the use of focused ultrasound (FUS) for biospecimen processing
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No. 1 scholarship grant for scientific training at INFN Structure of Roma for the following research topic: “Optimization of energy reconstruction in ECAL and its application into Higgs Boson measurements
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of these instruments to ensure their optimal performance and the accuracy of analytical results. Operate hot cells, fluidic systems, and purification systems within the quality and safety framework. Write, review
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experiments, behavioral research, econometric and causal inference approaches, optimization and analytical modeling, and data-driven techniques such as machine learning and large language models. Our work is