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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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Mesoscale Convective Systems (MCSs); organized systems of deep convective cells that can span 100 kilometres and persist over multiple hours. In tropical South America, 40-60 % of the rainfall can be related
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and is affected by various biogeochemical processes. The processes governing ocean alkalinity act over multiple timescales (from instantaneous chemical equilibration to hundred thousand of years) and
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forcing wind turbines offline or heatwaves and droughts reducing cooling water availability for thermal power generation. Of particular concern are compound energy droughts, where multiple stressors occur
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Professor Appy Sluijs, and close collaboration in this project will be with Dr. Peter Bijl. Multiple others will be involved for specific aspects of the project, including several scientists involved in
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research in TRL forward. Theoretical knowledge of, or experience with, machine learning such as representation and generative learning, and natural language processing. Programming skills, e.g. Python, Java
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/or human-computer interaction. Programming skills, e.g. Python, Java, or C++. Excellent command in English, verbal and written. Prior experience as a research assistant during (under)graduate studies
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and/or Python. Experience in, and aptitude for, complex statistical modelling (inc. mixed effects regression models and/or Bayesian statistics). Excellent written and spoken English. Desirable (traits