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computer simulations of coastal dynamics in a parallel PhD project conducted at WUR and provide context for visualisations of historic landscapes developed by a postdoc at NIOZ in a collaboration with
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); strong analytical and statistical skills; strong programming skills in R (or willingness to learn); robust methodological training in quantitative research methods; affinity with research on
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affinity for language data; solid programming skills (e.g., Python) and experience with machine learning or NLP, ideally including transformer-based models and word embeddings; excellent English
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performance over time. We're looking for a candidate with a strong background in epidemiology and quantitative methods, solid programming experience in R. The project is part of a national research program on
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engagement and participatory research with quantitative system modelling of our research group; experience with systems modeling and computer programming (e.g. Python); strong communication and scientific
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related discipline; An interest in the impacts of land use; Experience in handling spatial data; Programming experience in Python, and/or R; Proficiency in English; and The ability to work as part of
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; Knowledge on handling large scale datasets; Programming skills in Python and/or R; familiar with reproducible coding and automated (geospatial) data analysis; Familiarity or interest to dive into
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professional competence in quantitative and statistical methods, including applied econometrics and panel data analysis, proficiency in a statistical programming language such as R (preferably