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, enabling comprehensive simulation and analysis of quantum control strategies. Olav Tirkkonen will supervise the project at Aalto University, and Ülo Parts will act as thesis advisor. The ideal candidate
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large-scale social media analysis, smartphone-based sensing, and agent-based modeling. Combining macro-level patterns with micro-level behavioral data, it will examine how polarized content influences
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cleanroom fabrication techniques Proficiency with photonic simulation tools (PhotonDesign, Lumerical, COMSOL, or similar) Experience with optical characterization techniques (spectrum analysis, power
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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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two-dimensional materials by gate-tunable scanning tunneling microscopy (STM). Typical examples of these materials include van der Waals monolayers of transition metal dichalcogenide superconductors
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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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(generative models, real-time dashboards). Data analysis and geospatial tools (QGIS, ArcGIS, remote sensing). Visualization and communication tools (Adobe Creative Suite, Blender). Language & other skills
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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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, the candidate should have experience in several of the following topics. Experimental skills in microstructural analysis Experimental skills in mechanical testing (destructive or nondestructive) Computational
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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