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application! Work assignments Subject area: Computational studies of the influence of microstructural features on the structural integrity of metallic materials using machine learning Subject area description
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learning can improve software architecture recovery, how to optimize machine learning models at compile and runtime, and autonomous agents for software development. Part of the research is conducted through
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experiments, cutting-edge NMR spectroscopy and isotopomer analysis (doi: 10.1111/nph.20358). Two postdocs will work together to conduct plant ecophysiology experiments, and to analyze samples by NMR
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are focused drivers and enablers in our work. Our goal is to perform high quality research and education at bachelor, master and doctoral levels. The postdoc is expected to conduct high-quality research in a
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superconducting circuits. A part of the project is addressing specific challenges related to this goal. One such challenge is to efficiently read out quantum information from qubits. To achieve this, a first-stage
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initiative to develop a quantum computer based on superconducting circuits. Part of the project is also to solve specific problems related to this goal. A key challenge in this effort is mitigating errors in
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protocols, providing a detailed index to the taxonomic content of each sample. In DarkTree, we will use this material to systematically target the species-rich insect radiations that are not covered properly