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Field
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susceptible steel structures. Thus, the candidate will develop reliable machine learning-based surrogate models to replace expensive phase field models to simulate failure because of HE. The activities will be
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-specific inflammation” and aims to develop and apply advanced imaging tools to study immune cell dynamics in murine models of inflammation and cancer. More about our work: https://www.medizin.uni-muenster.de
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of future applications from the fields of structural lightweight construction, energy research and medical technology. The experimental development is closely accompanied by modelling approaches and
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29.04.2021, Wissenschaftliches Personal This PhD position is in the field of resource management for wireless network that leverage “digital twins” modeling aspects of the physical (such as user
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theories and numerical methods, carrying out and analysing field and remote sensing observations and conducting and analysing numerical model simulations. The PhD position is funded by the German Research
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identify the necessary solutions. The findings should also remain valid under different climate change scenarios. With its global state-of-the-art energy system model, ICE-2 at Forschungszentrum Jülich
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histological validation within murine cancer models. We offer an association with the Collaborative Research Centre 1450 “Insight – Multiscale imaging of organ-specific inflammation” graduate school
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now. As a result of this success and the dedicated community of plant enthusiasts, millions of plant observations are available, their numbers growing. These observations are useful for modelling
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) software for topology-informed biomedical image analysis and large foundation models. You will be responsible for Develop new machine learning algorithms for microscopy image analysis problems (2D/3D/4D/5D
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expertise in employing synthetic microbial communities, gnotobiotic mouse infection models as well as in molecular microbiology of gut microbiota and enteric pathogens. The TUM School of Life Sciences