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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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mentality. We are looking for you, if you have: a (research) master’s degree in Artificial Intelligence, Computational Linguistics, NLP, Computer Science, Data Science, or a related field, with a strong
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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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candidates with: An MSc degree in (or nearing completion of) an MSc program in Geoinformatics, Computer Science, (Quantitative) Geography, (Spatial / Geographic) Data Science, Environmental Science, or a
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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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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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; 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
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burial of microplastics and POC in currents down submarine canyons; incorporate these mechanisms into an existing computer model for sediment flux through submarine canyons; and validate the model on
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, you will evaluate the social feasibility of implementing solutions in real-world settings, working closely with partners like the Delta Climate Center and local stakeholders. Methods will include