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of paleoclimate modelling, starting as soon as possible. The position is funded for 36 months. Remuneration is in accordance with the German public tariff scheme (TV-L Brandenburg), salary group E 13. This is a
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integrating machine learning and domain-specific knowledge to predict failure arising from hydrogen embrittlement. You will carry out materials testing, computational model development, data processing, and
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highly motivated doctoral student to join an ambitious project aimed at building machine and deep learning models to study the genetics of human disease. Funded as part of the Helmholtz AI program, the
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- Model-based assessment of climate impacts on conflicting land use systems Reference code: 50139755_2 Commencement date: August 1st, 2025 Work location: Hamburg Application deadline: 04.06.2025 The Climate
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Programme description: The ICN2 offers a competitive PhD Programme to talented students who wish to develop a research career at one of the top European institutions in the field of nanoscience and
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with you on board! We are seeking a highly motivated PhD student to join our research team studying the role of NMDA receptors in psychosis, using translational mouse models of anti-NMDA receptor
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diverse academic backgrounds to contribute to our projects in areas such as: Network Security, Information Assurance, Model-driven Security, Cloud Computing, Cryptography, Satellite Systems, Vehicular
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diverse academic backgrounds to contribute to our projects in areas such as: Network Security, Information Assurance, Model-driven Security, Cloud Computing, Cryptography, Satellite Systems, Vehicular
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, traditional risk prediction models like the Steno Type 1 Risk Engine fail to account for the immunological dysregulation inherent in T1D. Project Objective The PhD candidate will primarily focus on the clinical
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Kolter, Tjibbe Donker and Philipp Henneke analysis of multiscale single cell ‘omics data in in experimental and human models reference genome and transcriptome assembly and annotation across species