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engineers to directly incorporate observed crack behaviour (shape, width, slip) into structural analysis and evaluation. The project combines experimental testing, advanced sensing, and multiscale modelling
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simulations using the method of Finite Differences in the Time Domain (FDTD), determination of optical material constants by multiangle UV-VIS-NIR ellipsometry, and/or characterization by UV-VIS-NIR
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implications for Africa’s urban future. It combines spatial analysis, political science, architecture, and urban studies to examine how vertical growth transforms cities environmentally, socially, and
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), Dakar (Senegal) and Luanda (Angola). Against the backdrop of accelerating verticalisation in African cities, VERTICAF offers the first systematic and diachronic analysis of how cities are expanding
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, human-environment interactions, sustainability science, and/or urban systems. Experience or strong interest in quantitative or mixed-methods research, such as survey design, statistical analysis, or
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work on the design, analysis, and implementation of innovative models for decision-making, economics, and operations. Research topics may include optimization, decision-making under uncertainty, market
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analysis in the framework for the project CARE (Cross-modal AI for Relief Efforts), a collaborative project between EPFL, ETH and the ICRC. You will innovate in foundational methods for jointly
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data analysis • Experience with plant physiological measurements, field ecology and/or remote sensing is an asset • Good quantitative and statistical skills • Familiarity with R
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and ice nucleating particles Data analysis of observations, numerical model output and remote sensing data Tight collaboration with the project partners and participation in working meetings Teaching
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in English (written and spoken) and willingness to work as part of a team Familiarity with Python, MATLAB or similar for data analysis Familiarity with numerical modeling tools (e.g. OpenSees, Abaqus