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on lignocellulose, ranging from nanomaterials to novel cellulose-based textiles. Your role and goals The doctoral researcher will be working in a project investigating metal cation coordination with cellulose
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mental health and computational social science, using large-scale social media analysis, smartphone-based sensing, and agent-based modeling. Combining macro-level patterns with micro-level behavioral data
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for a passionate and open-minded person with: A master's degree in energy technology, mathematical programming (e.g., Python), modeling, and optimization. Experience in geographic information analysis is
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the samples and of the measurement setups, cleanroom fabrication, performing cryogenic microwave measurements, and data analysis. You are expected to participate in advising and mentoring PhD students. Your
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scientific writing and communication skills very good knowledge of statistics and quantitative data analysis, hands-on experience with R or Python strong interest in prototyping commitment to and interest in
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analysis. Readiness to learn complementary skills, for example, environmental scientists learning computational design, or designers learning environmental field methods. Willingness to participate in
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visualization workflows (generative models, real-time dashboards). Data analysis and geospatial tools (QGIS, ArcGIS, remote sensing). Visualization and communication tools (Adobe Creative Suite, Blender