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analytics methods for the study of historical paintings in an interdisciplinary research environment. You will contribute to the development of state‑of‑the‑art methods that advance the analysis of complex
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, reliability, and availability of complex industrial systems while making maintenance strategies more cost-efficient. Together, UESL and IMOS are seeking a motivated and qualified PhD candidate to advance
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education in digitalization and electrification including renewable energy sources, electric vehicles, industrial IoT, AI, 6G communication and wireless sensor networks as well as research and education
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. More specifically, the doctoral program has four different specialization tracks: - Complex Systems and Networks (CN) - Computational Mechanics (CM) - Learning and Control (LC) - Software Quality (SQ
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rules in networks of complex spiking neuron models in the application field of geolocalization: Building up simulation model for networks of complex neurons with topologies close to neuroscience models
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plasticity platform. Different machine learning strategies will be explored to capture the complex relationships between microstructural features and mechanical responses. In particular, the project will
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within materials science and engineering. Use cases will be defined within different manufacturing techniques of lightweight structures to enable novel development of materials and process design. The PhD
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modelling, data assimilation, and multi-scale neural network architectures applied to spatio-temporal data. The development of these methods is motivated by a concrete and important application: inferring gas
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towards the next-generation co-design platform, accelerating the development cycle for complex interdisciplinary systems. Motivation Aircraft design is a highly complex process that must balance performance
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Application deadline: 21 May 2026 Apply now Today’s social media platforms are actors with a complex stake in shaping knowledge about global crises like climate change. Recent developments even reflect