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similar field; expertise in programming skills and statistical data analyses, including machine learning; affinity with environmental exposure modelling and high-performance computing; strong reporting and
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interest in environmental health and Exposome research; expertise in programming and quantitative data analysis, including machine learning in R/Python; affinity with bioinformatics; strong collaboration
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plan for and retire across more than one country due to factors such as health, climate amenities, socio-economic status, cultural values, and proximity to family, among others. These rapidly evolving
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investigates retirement experiences across countries, with a focus on the connections to the welfare state, family care networks, and the retirement industry. Today’s older adults are more likely to plan for and
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programming tools (e.g., Python, R, or MATLAB), ideally with experience working with spatiotemporally explicit datasets in raster or NetCDF formats. Familiarity with optimisation techniques such as mixed
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experience in programming and handling large (climatological) datasets. You are interested in the fundamental physical processes in Earth’s atmosphere and climate change; You are a team player. You have
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) physics, geosciences, meteorology, oceanography, or similar. You have strong programming skills (Python or similar). You have affinity with spatiotemporal data analyses, remote sensing and numerical
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fully funded, full-time, four-year PhD position within the Exposome-NL Gravitation programme external link . Your qualities You are a motivated and proactive colleague who: has a Master’s degree in
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this sparked your interest? We invite you to apply for our fully funded, full-time, four-year PhD position within the Exposome-NL Gravitation programme external link . Your qualities You are a motivated and
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formation via modifications to sedimentary redox reactions and sediment stabilisation, providing microenvironments favorable for organic matter preservation. A personalised training programme will be set up