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the preservation of cultural and historical values, and contribute to accessible, high-quality housing. The project will apply qualitative and participatory methods such as focus groups, interviews and workshops. A
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theoretical research, algorithm design, and the development of software tools that demonstrate the applicability of the new methods. Research environment The positions are hosted by the Department
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control and its integration with learning-based motion prediction under uncertainty. - Validate methods through simulation and collaboration with industrial partners (Volvo Cars and Volvo Group). - Publish
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Factors aims to enable users to live and work in a safe, meaningful, and sustainable way. This is done by adding knowledge about how people interact with technical artefacts, and by developing methods and
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of the numerical methods behind CFD and turbulence models. Experience in analyzing CFD data and interpreting simulation results. Excellent command of written and spoken English. Experience writing scientific reports
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developing AI methods for automated microstructure analysis and 3D microstructure generation. By combining self-supervised learning and diffusion-based generative models, the goal is to: Reconstruct high
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, thermal dynamics, and charging strategies. Validate methods through simulation and collaboration with industrial partners (Volvo Group). Publish results in leading journals and present at international
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Technology (Maria Taljegård). Main responsibilities Plan and perform research under the guidance of supervisors Apply and develop energy- and environmental systems assessment methods and tools Collect and
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both qualitative and quantitative methods, e.g., case studies, interviews, applied analytics, and field experiments. By developing new theories and applications, you will have the opportunity to solve