85 machine-learning "https:" "https:" "https:" "https:" "https:" "https:" "https:" "Univ" scholarships at Forschungszentrum Jülich in Germany
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opportunities specifically for doctoral candidates (JuDocS): https://go.fzj.de/JuDocs HEALTH & WELL-BEING: Your health is important to us. You can look forward to a comprehensive company health management
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quickly settle into the team and are given structured training for your tasks. We also support you from the very beginning and make your start easier with our Welcome Days and Welcome Guide: https
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energy system models based on the institute`s own open-source FINE framework https://github.com/FZJ-IEK3-VSA/FINE. Your tasks in detail: Implementing geothermal plants with material co-production in
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international project partners, embedded in an ERC-funded project. For deeper insights, please have a look at our institute website: https://www.fz-juelich.de/en/pgi/pgi-7 and the research group in which
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: Your professional development is important to us – we support you specifically and individually e.g., through training and networking opportunities specifically for doctoral candidates (JuDocS): https
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development 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/JuDocs SUCCESSFUL START: It is important to us that you quickly settle into the team and are given structured training for your tasks. We also support you from the very beginning and
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Infrastructure? No Offer Description Work group: IAS-8 - Datenanalyik und Maschinenlernen Area of research: PHD Thesis Job description: Your Job: We are looking for a PhD student in machine learning to work within
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models, which are essential for understanding climate change impacts. The work involves reviewing existing modeling and model–data fusion techniques, and developing faster, machine-learning–based tools
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modeling and model–data fusion techniques, and developing faster, machine-learning–based tools that can stand in for slow model simulations. These tools will be used to test how model parameters influence