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platform-specific physics knowledge, be it in ultracold neutral atoms, trapped ions or superconducting qubits. This may also involve investigation of the decoherence processes and related question
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-the-loop exploration of extreme-scale scientific data. This position sits at the intersection of scientific visualization, agentic AI systems, human–computer interaction (HCI), and high-performance computing
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microenvironment. The project will employ genetically engineered mouse and human glioma models, along with advanced imaging techniques, single-cell and spatial transcriptomics, and molecular biology approaches
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conferences. A PhD in Chemistry, Materials Science and Engineering, Physics, Nanoscience and Nanoengineering or equivalent is required. Prior experiences with electron microscopy, electrochemistry
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QUALIFICATIONS: PhD in computer science, electrical/biomedical engineering, statistics, applied mathematics, or a related field. Strong track record in machine learning/deep learning with imaging data
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University of North Carolina at Chapel Hill | Chapel Hill, North Carolina | United States | about 2 months ago
. Research includes but is not limited to: in vitro cell culture experiments, transport assays, Western Blotting, cloning and mutagenesis, immunohistochemical imaging and live cell imaging, LC-MS/MS