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scientific programming and numerical / statistical analysis of simulated and observed data. Candidates should be able to demonstrate motivation and a strong eagerness to learn, and have the ability to both
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MSc in physics, applied mathematics, environmental sciences, computational science or a related field; excellent skills in scientific programming and numerical/statistical analysis of simulated and
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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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comfortable applying analytical thinking to explore research questions and have programming experience (preferably in Python). You have an affinity with coastal numerical modelling, e.g. AeoLiS, XBeach
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science, mathematics, physics, or a related field. You have affinity with numerical modelling, preferably atmospheric modelling or climate modelling, and mathematical theory of dynamical systems. You have
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an independent, highly motivated team player, having experience in numerical modelling, and have completed your MSc degree in Earth Sciences, Oceanography, Climate Sciences or a related discipline by the time the
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sea ice melting along these paths; performing numerical model simulations to explore how changes in winds, ocean temperatures, and other factors affect sea ice in the present and future. You will be
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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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densification model forced by high resolution output from the regional climate model RACMO to simulate the evolution of the Larsen C firn layer in the recent past (1950 to present) and into the future (up to 2100
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; excellent skills in scientific programming and numerical / statistical analysis of simulated and observed data; basic knowledge of (geophysical) fluid dynamics; excellent writing and communication skills