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focus on quantum channel discrimination for high-resolution spectroscopy and AC field sensing. The project aims to develop theoretical frameworks for distinguishing closely related quantum processes
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complex systems. Development and application of theoretical tools that combine experimental data and atomistic computer simulations to provide a comprehensive picture that is difficult to achieve through
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frameworks for distinguishing closely related quantum processes that arise in light-matter interactions, and to use these frameworks to extract fine spectral or temporal information from weak or structured
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imaging and microscopy-based analysis for drug response validation. Experience in mass spectrometry-based proteomics, transcriptomic and other omics-based workflows, including sample preparation, analysis
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have familiarity with super-resolution and high-content imaging and microscopy-based analysis for drug response validation. Experience in mass spectrometry-based proteomics, transcriptomic and other
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transistors to solve some of society’s most pressing computational challenges. Silicon-based approaches to quantum information processing offer advantages for scaling such as high qubit density, record qubit
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frameworks for distinguishing closely related quantum processes that arise in light-matter interactions, and to use these frameworks to extract fine spectral or temporal information from weak or structured
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focus on quantum channel discrimination for high-resolution spectroscopy and AC field sensing. The project aims to develop theoretical frameworks for distinguishing closely related quantum processes
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the scientific and administrative capacity of ISSP UL by establishing high-level research culture, processes, and excellence indicators. Expand national and international collaborations with top research centres
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Manufacturing and/or AI Robotics. Focus areas include: yield/defect causal analysis and XAI; process-variation monitoring and root-cause analysis; intelligent scheduling/dispatching for WIP/throughput (multi