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, climate physics, geosciences or a related field; excellent skills in scientific programming and numerical / statistical analysis of simulated and observed data; a versatile mind and openness to work on a
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the DROPapp by integrating local and scientific knowledge. In this project, you will integrate the local forecasts based on observed local ecological indicators and scientific forecasts based on numerical
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satellite observations, climate reanalysis data, and numerical models to better understand how sea ice is transported out of the Arctic and how heat is exchanged between the ocean, ice, and atmosphere. Your
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an overview of your experience with molecular dynamics, density-functional-theory, machine learning, coding skills, theoretical solid mechanics, numerical analysis. The official transcripts of your BSc and MSc
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-theory, machine learning, coding skills, theoretical solid mechanics, numerical analysis. The official transcripts of your BSc and MSc grades List of at least two references with full contact information
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related field; experience with numerical modelling, preferably hydrological modelling; affinity with delta systems, adaptation and policy analysis; motivation to work in interdisciplinary scientific
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adaptation by strengthening energy system resilience against growing climate-related risks. Modeling energy systems presents numerous challenges, which become increasingly intricate when applied at urban
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(ELF). You will therefore collaborate intensively with international partners for support, and measurement analysis will be an integral part of your job. Your qualities You are an enthusiastic and
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between these important climate subsystems, using models of different complexity and a combination of mathematical, numerical and data analysis methods. You can find the other vacancy at PhD Position in
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-related risks. Modeling energy systems presents numerous challenges, which become increasingly intricate when applied at urban or local scales due to spatial, temporal, and sectoral heterogeneities