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Field
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analysis, modelling and field experiments, our project will illuminate the way forward for assisted migration (AM) as a pathway to sustain, and to restore in case of degradation, the biodiversity and
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link structure-property relationships from DFT, MD, phase-field, TEM/SEM, and other multimodal datasets from simulation and experiment Develop benchmarking protocols and toolkits to evaluate AI models
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Environment (VTE) for disaster response simulation, integration of Building Information Modelling (BIM) with Structural Health Monitoring (SHM) using smart sensor networks, and resilience-informed design
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computing to develop a continuous and local alternative to existing gradient-based learning rules, bridging theories of predictive coding with event-based control/ Simulate models of the learning algorithm
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Virtual Training Environment (VTE) for disaster response simulation, integration of Building Information Modelling (BIM) with Structural Health Monitoring (SHM) using smart sensor networks, and resilience
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at the nanometer scale. We will use available DNA thermodynamic database, coarse-grained simulations of DNA motifs, and existing experimental data to establish an AI model that is able to guide the construction
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manufacturing (3D printing) techniques. The purpose of the studentship is to develop a next-generation in vitro model of aged human skin to evaluate the cytocompatibility of materials used in maxillofacial
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Vacancies PhD position in Numerical Modeling of Thermo-Mechanical Effects for High-Performance Mechatronics Key takeaways A PhD position is available at the chair of Precision Engineering at
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motion and the viewing perspective of the observer (Nikolaidis et al, 2016). This project will develop continuous models of action legibility using these sources of information from data collected in a
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models that integrate data from quantum simulations and experiments, using techniques such as equivariant graph neural networks with tensor embeddings. We aim to train these methods in a closed-loop