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Helmholtz Zentrum München - Deutsches Forschungszentrum für Gesundheit und Umwelt | Stein bei N rnberg, Bayern | Germany | 2 months ago
to data analysis, functional interpretation, and publication. Your tasks Develop and investigate independent, hypothesis-driven research questions related to cross-organ metabolic and hormonal processes as
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energy system is undergoing a fundamental transformation driven by the rapid integration of renewable energy, electric vehicles and large-scale AI data centers. Power electronic converters play a pivotal
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Where will you work? You will be appointed at TU Delft and work within a research group with strong expertise in vascular access, large animal models and clinical translation. At the same time, you will
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health. Successful candidates may have experience in electron or X-ray microscopy, image analysis, AI and machine learning, quantitative data science or computational modelling. They will be able to work
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of video and low-cost sensor technologies to capture subtle movement patterns, creating a rich dataset for AI-driven analysis. Machine learning, deep learning, computer vision and multimodal AI methods will
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develop advanced models, algorithms, and control solutions for simulating, optimizing, and operating future integrated energy systems. We address the challenges arising from the increasing integration
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sensors - if we can control and tune their properties. You will develop and use top-of-the-line machine learning models to predict the sensor response of these materials under realistic conditions
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to developing methods for iPSC culture, 3D cell models, and stem cell differentiation within the field of complex tissue regeneration. In this PhD project, you will work at the interface of stem cell biology
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to developing methods for iPSC culture, 3D cell models, and stem cell differentiation within the field of complex tissue regeneration. In this PhD project, you will work at the interface of stem cell biology
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Title: Beyond the Ball: A Modular Physics Sandbox for Investigating Aerodynamic and Projectile Modelling, Vehicle Dynamics and Adaptive Networking. PhD Studentship: R-LINCS2 funded. The Studentship is