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such mechanisms contribute to improved damage tolerance at the structural level. You have experience with integrating advanced damage models into numerical simulation frameworks, and you are able to develop
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, and energy demand. In particular, you will: Develop an integrated, system-level digital-twin framework connecting electrolyzer models with relevant Power-to-X components and energy-systema. Develop
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hindering factors for scaling, including market conditions, policy frameworks and local infrastructures. You will work closely with colleagues in the Materials Science and Engineering research group and
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of the project's conceptual framework on school emotions and not liking school and participate actively in an interdisciplinary research environment that brings together educational history, history of emotions
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perception, optimization, or control will be an advantage. The candidate should be comfortable with scientific programming, for example in Python and common machine-learning frameworks such as PyTorch
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of research within the field. As part of the application, applicants are expected to outline a project description (min. 5 pages, as mentioned below) in which the applicant suggests the framework for such a
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role in developing and implementing novel computational models within a boundary element framework, coupling the BEM with models for flow separation, viscous drag and cavitation. There is room to shape
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large language models in distributed environments while safeguarding both model integrity and data confidentiality. The successful candidate will develop novel frameworks that enable effective
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this context, energy sector organizations are turning to AI to forecast, balance, and manage critical infrastructure, while also responding to new regulatory frameworks such as the EU AI Act. ORBIT examines how
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. Within the framework of the position, there will typically be opportunities to participate in relevant conferences and workshops and to build an international network within solid and computational