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applications towards materials science. Generative machine learning models have emerged as a prominent approach to AI, with impressive performance in many application domains, including materials discovery
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plasma model (www.amitiscode.com ). By comparing model results with NASA’s MESSENGER and ESA’s/JAXA’s BepiColombo observations, the research aims to deepen our understanding of Mercury’s magnetosphere
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7 industrial PhD students. During the course of the DDLS program more than 260 PhD students and 200 postdocs will be part of the Research School. The DDLS program has four strategic research areas
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transformation of SMEs through cutting-edge digital innovation and circular business models. Your work will help empower companies to decarbonize, minimize waste, and build resilient, future-proof value chains
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, flexible and adaptable distributed system of systems. Example of specific problems are: -Information interoperability supported by ontologies. -Unified data models for operational environmental impact -SOA
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Living Labs, addressing real-world challenges through digital and physical infrastructure. - Governance models for Living Labs, ensuring sustainable multi-stakeholder collaboration and transparent
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of this WASP-financed project is machine learning, in particular dealing with generative models and instabilities associated with cycles of retraining on mixtures of human and machine-generated data
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be paid to the following experiences: -Experience in sampling and analyses of building materials -Experience in Life Cycle Analysis in construction sector. -Experience in building information modeling
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. Programming gene circuits Modeling and designing synthetic DNA components Construction of Chemical Reaction Networks (CRNs) Simulation and analysis using MATLAB and Visual DSD Robust analysis of various modules
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in humans and in animal models. Environmental factors have been reported to predict the risks of developing SUDs too. For instance, epidemiological data have shown that impoverished social environments