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will start in Leiden, transfer after a year to Lund for two years, with a final year in Leiden. You will consider nonlinear wave equations with spatial inhomogeneities and use tools from dynamical
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primarily computational, working with long-read, short-read, single-cell and spatial transcriptomic data. The successful candidate will develop reproducible analysis workflows; analyse long-read RNA and DNA
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interest in data analysis, modelling, statistics, and machine learning. Experience in spatial data analysis (GIS), scientific programming (Python, R, or equivalent), or artificial intelligence will be
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Section of the Department of Human Geography and Spatial Planning, with close collaboration with the Innovation Studies Section at the Copernicus Institute of Sustainable Development. Both groups
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is rising and empirical evidence is growing. Yet, we still lack systematic ex-ante and ex-post quantitative assessments of adaptation effectiveness and limits across various scales (temporal, spatial
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-offs and synergies of land use decisions desirable Good knowledge of statistics and relevant software products (R, SPSS, jamovi or similar) Good knowledge of analysing spatial data (geoinformation
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analyze temporal dynamics using time series methods and statistical techniques, and you will explore spatial variability using suitable modelling and data analysis approaches. A central task will be
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with regard to both spatial and temporal evolution. • Investigate mechanisms controlling radionuclide retention and transport in cementitious and geological materials. • Assess the influence
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for efficiency monitoring and fault detection, combining sensor data, system layout knowledge, and physical principles to extract spatial-temporal features and predict equipment behaviour; 2) Statistical anomaly
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engineered and natural environments relevant for nuclear waste management with regard to both spatial and temporal evolution. • Investigate mechanisms controlling radionuclide retention and transport in