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Field
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. The main activities include: Designing machine learning models that can detect unusual, unsafe, or attacked operating conditions. Developing data-driven models that capture how faults and attacks spread
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assurance, data science, data-driven modelling, digital manufacturing workflows, and Digital Product Passport B.3 Hands-on experience in machine learning, ontologies and knowledge graphs, IIoT and digital
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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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seeking a doctoral researcher possessing a curious and self-driven mindset to develop and apply new simulation protocols to push towards realistic and dynamic modeling of AS-ALD processes. Recently, we have
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, and materials science. In this PhD project, you will: § Develop an experimental platform to study 3D self-organization of active particles. § Fabricate and characterize light-driven microswimmers
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environmental disciplines, as well as for its interdisciplinary work. The mission of the institute is to contribute to sustainable development and care for the environment through scientific research and teaching
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infrastructure. Prominent examples include energy and transportation networks, which are undergoing a profound transformation driven by renewable energy integration, battery storage, ubiquitous computation and
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This PhD redefines electromagnetic sensing by moving beyond magnetic permeability-dominated approaches to establish a conductivity-driven eddy-current framework for tracking microstructural
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structural glycoproteomics. For development and translational research we make use of patient samples and models with defined genetic and/or biochemical defects that require structural glycoproteomics
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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