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Zeppelin airship Apply advanced data analysis methods, including statistical tools and programming, to large multidimensional datasets from chamber and airborne experiments Present your results
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, including statistical tools and programming, to large multidimensional datasets from chamber and airborne experiments Present your results at international conferences and publish them in peer-reviewed
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problems Proficiency in data analysis and programming using at least one statistical program such as R, Python, or similar programming languages Experience with GAMS, GTAP, and Exiobase is an asset. Skills
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algorithms, computational complexity theory, and information theory Relevant coursework and experience in spiking neural networks, and statistics A strong electronics background, including experience in
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quantify model uncertainties For further information visit our website http://www.fz-juelich.de/ibg/ibg-3/EN/Home/home_node.html or contact us via the contact form. Your Profile: Master’s degree in
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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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is important to us – we support you specifically and individually e.g., through training and networking opportunities specifically for doctoral candidates (JuDocS): https://go.fzj.de/JuDocs • SUPPORT
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: https://go.fzj.de/equality and on specific support options: https://go.fzj.de/womens-job-journey
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Approach ( https://vhrz669.hrz.uni-marburg.de/ssf/ ). Understanding the mechanisms controlling subsurface flow (SSF) and the conditions under which it occurs remains a major challenge in hydrology and
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NEST: https://nest-simulator.readthedocs.io Your tasks in detail: Work with the NEST main code base and experimental branches Dissect the spiking network simulation cycle into phases and capture the flow