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Your Job: This PhD project focuses on modelling and simulating future gas grids, exploring transformation pathways, and developing cross-sectoral simulation frameworks to support informed decision
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25.11.2025 Application deadline: 10.12.2025 For the research data management initiative German Human Genome-Phenome Archive (GHGA) a research position as Technical Data Steward/ Bioinformatician (m
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biology (evolution). The core responsibility of the position is the research-based design, development, and empirical evaluation of the AI tutor. This includes modeling learning-supportive interactions and
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understood the data protection information provided by TUM. The position is suitable for disabled persons. Disabled applicants will be given preference in case of generally equivalent suitability, aptitude and
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project position as Research Associate / PhD Student (m/f/x) within the MSCA Doctoral Network SLICE (due to funding, the salary is calculated according to MSCA regulation) starting October 1, 2026
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Is the Job related to staff position within a Research Infrastructure? No Offer Description Work group: Institute of Material Systems Modeling Area of research: Scientific / postdoctoral posts Starting
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). The institute also maintains locations in Dedelow and Paulinenaue. The position will be based in the Research Platform “Data Analysis and Simulation“ within the Working Group “Ecosystem Modelling“ under
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highlight the potential of microbiome intervention in immuno-oncology. In our team, we actively integrate translational data, functional assays and preclinical models, to understand and overcome mechanisms
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Deutsches Zentrum für Neurodegenerative Erkrankungen | Ulm, Baden W rttemberg | Germany | 8 days ago
staff position within a Research Infrastructure? No Offer Description Area of research: PHD Thesis Job description: We are looking for you to join us full-time for a position that is initially limited
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its maintenance and safety increasingly depend on data. This PhD project will develop new methods that combine remote sensing, physics-based modelling, and Bayesian machine learning to support risk