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energy technology adoption in housing in Lausanne. An interdisciplinary agent-based model (ABM) has been developed to represent the energy transition at the level of Lausanne, integrating not only
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have recently been developed in the Roke lab and used to image in real time interfacial water and electrostatic potentials on membrane interfaces of model membranes and in living cells. We will use
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students who will contribute novel multimodal generative AI architectures, latent diffusion processes, and reinforcement learning approaches. Interestingly, the proposed model will interface with an
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, hydrological and land-cover data, and applying approaches such as the InVEST Urban Cooling Model and relevant flood-analysis methods. Coordinate field measurements and model validation along selected
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and ice nucleating particles Data analysis of observations, numerical model output and remote sensing data Tight collaboration with the project partners and participation in working meetings Teaching
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simulations software such as COMSOL or CST. Characterize samples in the lab. Model experimental data from first principles using Matlab/Python codes. Write scientific publications, file patents, disseminate
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guidelines for the efficient and automated design and optimization of small-scale turbomachinery. Required competences Strong background in model order reduction techniques, surrogate modeling
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PhD Student Position in Interoperable Digital Workflows for Regenerative Building Design and Perform
. Using Smart Living Lab datasets and infrastructure, you will undertake full-scale testing, data collection, model calibration and scientific validation in Fribourg. You will compare predicted and