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deadline: 17 March 2026 Apply now University School of Economics offers a fully funded PhD on the economic aspects of water-resilient landscapes. The project develops a comprehensive economic analysis of
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. The PhD candidate will be based in the Molecular Epidemiology and Data Science Group, led by Dr. Natalia Vilor-Tejedor, and will collaborate with researchers in epidemiology, neuroscience, data science, and
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qualitative data to study how parents’ social network connections and resources shape their children’s career outcomes. As a PhD candidate, you will work on your own project within the SHINE programme. The aim
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interest in and experience with analysing quantitative survey data, e.g. multilevel regression and longitudinal panel analysis, using SPSS, Stata, or R. You have an excellent command of Dutch (for collecting
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negative caregiver outcomes. Methodologically, the project combines quantitative and qualitative approaches and builds on high-quality Dutch data sources. The PhD candidate will conduct multiple empirical
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existing datasets and set up new studies, collecting samples from horses and performing laboratory experiments followed by data analysis. Techniques such as 16S rRNA sequencing, shotgun metagenomic
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and clinical populations (e.g. stroke, brain tumour and neurodegenerative conditions). You will contribute to data preprocessing, and advanced analysis, including tractography, network modelling and
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for different water and land users, livelihoods, and landscapes. In collaboration with various societal and academic partners in Indonesia and the Netherlands, the PhD candidate will include an analysis
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Investigator (PI), Dr Marzi. Together, you will further develop and refine the PhD case studies, the research approach and the various work packages, as well as analyse data, participate in conferences and
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, or similar) for data analysis and modeling; Theoretical background and genuine interest in porous media processes, such as fluid flow, reactive transport, soil-fluid interactions, or geomechanics; Excellent