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a comprehensive multi-perspectives analysis approach, essential to track the impacts of the characteristics in different scales of the investigated processes on their overall techno-economic
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protons are present and accelerated, or an admixture of the two. The composition affects the power of the jet and the presence or lack of hadrons is a crucial ingredient in modelling the multi-wavelength
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research element. Experience in teaching statistics and business analytics in a business school environment will be considered an advantage. The lecturer is expected to conduct research and follow
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monolayers of transition metal dichalcogenide superconductors, Mott insulators, ferromagnets, multiferroics, etc. Your tasks will include: Fabrication of nanoelectronic devices in cleanroom facilities
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by integrating computational mental health and computational social science, using large-scale social media analysis, smartphone-based sensing, and agent-based modeling. Combining macro-level patterns
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characterization techniques (spectrum analysis, power measurements, linewidth analysis) Knowledge of semiconductor laser physics (thermal effects, carrier dynamics) Experience with mask layout design Knowledge
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. Design, test, and document computational frameworks that combine 4D point cloud data, geospatial analysis, and advanced ML/DL algorithms. Integrate dynamic environmental datasets into immersive and
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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