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perform quantitative hydrogen analysis using electron spectroscopy. Main task of the PhD student is to establish the scientific basis for high-resolution electron recoil spectroscopy for surface hydrogen
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of measurement systems, signal processing and analysis and the assessment of measurement accuracy, robustness and long-term stability. The resulting data form the basis for model-based approaches to evaluating
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multifractal analysis, urban and energy planning, geography, and artificial intelligence to develop coherent and resilient approaches for urban energy infrastructures under land-use constraints such as No Net
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analysis of large datasets, high-throughput metabolomics, time-lapse microscopy, to investigate how to pharmacologically interfere with fundamental mechanisms in the regulation of cancer metabolism
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with data analysis/modelling and programming (R or Python). Advantageous: geostatistics, digital soil mapping, remote sensing, GIS, big data or cloud tools. Proactive working style, strong communication
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analysis of large datasets, high-throughput metabolomics, time-lapse microscopy, to investigate how to pharmacologically interfere with fundamental mechanisms in the regulation of cancer metabolism
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have the opportunity to exploit some of the cutting-edge experimental and computational methods, comprising constraint-based and kinetic modeling, statistical analysis of large datasets, high-throughput
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collaboration funded by the French National Research Agency (ANR) and the Swiss National Science Foundation (SNSF). The project brings together expertise in multifractal analysis, urban and energy planning
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talented candidate with a Master’s degree in civil engineering, mechanical engineering, or a related discipline Solid background in mechanics of materials and finite element analysis Sound knowledge
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applications in forecasting, system optimization, flexibility management, and resilience analysis. The work will be carried out in close collaboration with our interdisciplinary teams at both Empa and EPFL, as