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at the Niels Bohr Institute, Faculty of Science, University of Copenhagen. We are located in Copenhagen. We offer creative and stimulating working conditions in a dynamic and international research environment
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with host bacteria during infections, particularly focusing on the use of E. coli and its related phages as model organisms. However, the results may be applied in pathogenic bacteria related to E. coli
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inductive biases, we aim to identify key mechanisms that drive rapid learning in the visual system. The goal is to create a robust mechanistic neural network model of the visual system that not only mimics
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. Extending the model to full two-way coupling, allowing feedback from flexible vegetation on wave-induced flow. Applying the fully-coupled model to simulate interactions under both regular and irregular wave
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species like birds and bats. Combining PAM with occupancy modeling allows for large-scale ecological studies, assessing both individual species and community responses to environmental changes. In this 4
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on these materials, which will be used to implement high frequency and high efficiency IVRs for HPC applications. Objectives:-Fabrication, characterization and modeling of the composite magnetic materials.-Modeling
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, engineers and PhD candidates. The PhD candidate is expected to develop an advanced engineering noise prediction model for efficient computation of sound propagation in a range-dependent atmosphere where
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hydrogen storage tanks. This PhD vacancy is focused on the finite element modelling and design of the pressurized composite tank, in different operational conditions (static burst, fatigue and impact). The
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tasks will be to: Develop and implement machine learning models for dynamic simulations of renewable power systems Develop comprehensive guidelines for verifying and testing dynamic equivalents Integrate
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the molten pool. However, these models are computationally intensive and impractical for widespread simulations of large-scale part deposition. This project aims to develop a novel FEA-based approach