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Field
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of the German language is considered an asset Since the work involves interdisciplinary cooperation with several researchers and technicians, good communication and organizational skills are essential Driver’s license and
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modelling, analysis of complex dynamical systems, simulation, analysis of large-scale datasets with machine learning methods, and software development are beneficial Good organisational skills and ability
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team across institutes Very good communication and organizational skills Very good command of the English language (at least B2 level according to the CEFR: https://go.fzj.de/languagerequirements
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studies in the field of forestry, ecosystem management, simulation modeling or related fields Interested in the diversity and resilience of forests Knowledge on forest ecosystem service provisioning Good
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). The envisioned contract starting date is flexible between 07/2026-12/2026. For further details on the group, see https://www.uni-saarland.de/lehrstuhl/munz.html . Please include in your application your CV, a 1
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geophysics, physics, geoscience, computational geoscience, or related natural sciences with an overall grade of at least good Experience in programming (e.g., MATLAB, Python, C/C++) Advanced knowledge
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University of Munich - Good knowledge of the operating principles of energy storage, specifically hydrogen technologies (electrolyzers, fuel cells) and battery systems. - Experience in modelling, system
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Knowledge on forest ecosystem service provisioning Good quantitative skills, specific interest in simulation modelling Good communication skills Ability to work in an interdisciplinary team Your tasks You
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evaluate usability of system architectures such as Retrieval-Augmented Generation (RAG) for data retrieval and knowledge inference - implementation of your machine learning pipeline in Python (using e.g
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in geochemical or thermodynamic modelling is desirable Ability to work collaboratively within a multidisciplinary and international team Very good command of written and spoken English with extensive