15 computational-modelling PhD positions at Chalmers University of Technology in Sweden
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machine learning, computer vision, and materials science. The focus of this position is on development of neuro-symbolic models for the effective behaviour of the complex microstructure of recycled
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with expertise in materials characterisation, computer vision, computational modelling, and machine learning. The other PhD positions connected to the project are: PhD Student Position in Generative
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student, you will be supported by a multidisciplinary team with expertise in materials characterisation, computer vision, computational modelling, and machine learning. The other PhD positions connected
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cross-layer defenses that ensure secure and efficient AI model development at scale. Information about the division The department of Computer Science and Engineering is strongly international, with
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Computational Arts, Music, and Games within the DSAI division. About the research project This position is related to investigating learned cultural representations in data search spaces of generative AI models
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for advanced courses, international research visits, and networking across Sweden’s top universities. Information about the research group The Computer Vision Group at the division of Signal processing and
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computational facilities for testing & modelling natural clays and access to data on natural slopes in Western Coast of Sweden. These state-of-the-art resources empower you to conduct cutting-edge research with
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the role of toe erosion in triggering landslides in sensitive clays. The focus will be on developing computational models that will quantify the erosion mechanisms, precursors and the time to failure
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for Sustainable Housing and buildings”, you will: Develop an ontology of regenerative building production by analyzing how regeneration affects on-site praxis, economic structures, and business models and
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We are looking for a highly motivated, skilled, and persistent PhD student with experience in computational fluid dynamics (CFD) and some knowledge in structural analysis. The research aims