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group 13 TV-L . Your challenge Your main task within the framework of the “Aerospace Knowledge Base: Linked (Semi-)Open Data for AeroSpace Engineering” project, funded by the Lower Saxony Ministry of
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). The advertised position is primarily linked to the study of metal atoms and aerosols in the middle atmosphere and their relation to the re-entry of space debris at mid-latitudes (Kühlungsborn, Germany) and high
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research in the broad field of computational methods for the built environment. Particular emphasis is placed on building information modelling, digital drawings, point cloud capturing and processing as
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) to work on the development of an Amazonian Early Warning System (AmEWS) integrating Earth Observation data, process-based ecosystem models, and advanced machine learning approaches. The position is embedded
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CV, cover letter, and contact information for two references, to Prof. Elmar Schiebel at schiebel.elmar@zmbh.uni-heidelberg.de . The PhD student will be a member of the Heidelberg Biosciences
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information and instructions please go to the following link . Please take notice of the following rules: At the time of application, your last final exam should have taken place during the past six years
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that you have acknowledged the above data protection information of TUM. Kontakt: shadi.albarqouni@helmholtz-muenchen.de More Information https://albarqouni.github.io/team/
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information). If applicable: List of relevant projects and publications. Optional: A letter of recommendation from your MSc thesis supervisor. Applications will be reviewed starting 30 April 2026 and will
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focuses on developing information theory, coding schemes, and other algorithmic methods for DNA data storage. Here is a video on the topic: https://www.bbc.com/future/article/20151122-this-is-how-to-store
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principles, kinetic Monte Carlo, machine learning) will be applied to investigate diffusion phenomena and link speciation with spectroscopic signatures. Formal requirements include a Master's degree in