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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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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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-of-the-art computational resources, enabling advanced simulations and modeling. Moreover, we actively collaborate with leading experts in laser diagnostics, automatic control, heat transfer, and life cycle
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epidemiology to understand RNA metabolism. Perform stochastic simulations to analyze model behaviors. Fit the model parameters to empirical RNA expression and RNA-protein binding data. Predict outcomes
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reacting flows. A novel aspect of the project is the use of highly perturbed laminar flame simulations to inform CFD modelling of turbulent combustion in lean hydrogen-air mixtures. Experimental work will be
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educational programs, we are now seeking a postdoctoral researcher to work on privacy for data-driven models and high-dimensional data. The position is full-time for two years, starting on 1st September, or as
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networks are controlled, to develop predictive models of methane cycling in northern rivers. This postdoc position will focus on assessing how stream methane emissions are linked to permafrost thaw, using
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design. One of our group's goals is to create efficient surrogate models that reduce the computational cost of MD simulations by several orders of magnitude. Notable examples of our work in this area
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models into Chalmers’ bridge simulators in collaboration with other researchers. You are also expected to supervise PhD and MSc students and to publish at least two peer-reviewed journal articles during
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systems, or network analysis. Experience with methods for causal inference, or modelling of biological systems is also considered a merit, along with prior work involving large-scale sequencing data such as