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modeling, secure data exchange, and reconfigurable production architectures. The research is carried out in collaboration with leading industrial and academic partners within large-scale Horizon Europe
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to the development of methodologies for modelling, predicting, and validating dynamic interactions through numerical simulations and field measurements. This project is funded by The Swedish Transport Administration
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focus is the interplay of these factors with mitochondrial translation systems and respiratory chain complex assembly. We use the yeast Saccharomyces cerevisiae as our primary research model. In
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finite element modeling as the foundation of a comprehensive design framework that integrates simulation, experimentation, and machine learning. Fall-related injuries are a leading cause of morbidity and
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of quantum-chemical simulations are strongly desired. The candidates experienced in software for photophysical simulations (MOMAP, FCclasses, or custom handmade codes) are prioritized. In order to communicate
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with industry, academia, authorities, and insurance companies. Main responsibilities Computational Modeling and Simulation Develop and validate finite element models using LS-DYNA, OpenRadioss
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patterns of genomic sequences, with applications ranging from biogeographical mapping to paleogenetic reconstructions. The candidate will work jointly with Dr. Eran Elhaik to design machine-learning models
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sequences, with applications ranging from biogeographical mapping to paleogenetic reconstructions. The candidate will work jointly with Dr. Eran Elhaik to design machine-learning models that unlock
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. Eran Elhaik to design machine-learning models that unlock the potential of genomics for forensic investigations and historical reconstructions. Work duties We aim to develop machine learning methods
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improve models and codes for assessment of the liquid source term during severe accident (SA) of LWR systems. In particular, research will include assessment of the characteristics of the containment water