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to study and predict. In this four-year SNF-funded project, you will develop data-driven, multiscale simulation methods that combine computer simulations, machine learning, and surrogate models to explore
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plumes from point sources using the MicroHH atmospheric model. Analysis of plume dynamics and NOx chemistry in the high-resolution simulations. Develop and refine data-driven methods for emission
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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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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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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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, including the use of CRISPR-engineered cancer cell lines and metastatic models. In addition, the project integrates high-throughput metabolic profiling of genetic perturbations, computational data analysis
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-on mouse experience will not be considered. The project also includes high-throughput metabolic profiling of genetic perturbations, computational data analysis, and next-generation sequencing (NGS) of pooled
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modelling and analysis is a strong asset. You are proficient working with programming languages such as Python, MATLAB, or similar, and are interested in combining analytical modelling with data-driven or AI