148 evolution "https:" "https:" "https:" "https:" "https:" "https:" "The University of Manchester" positions at Chalmers University of Technology in Sweden
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strategic areas: cell and molecular biology, evolution and biodiversity, precision medicine and diagnostics, epidemiology and biology of infection. For more information, please see www.scilifelab.se/data
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international academic institutions and 14 industry partners (https://euraxess.ec.europa.eu/jobs/401249 ). We work together in the field of fluid-structure interaction in technical systems and industrial
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, learning and outreach. The research topics at the department span from fundamental to applied research with the aim of contributing to the development of a sustainable society. A wide range of experimental
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for the future industry in a sustainable society. Through excellent research, innovation, and education, we contribute to the development of future industrial value chains. In the division of Computational
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machine learning on large epidemiological cohorts, diet and health data analysis of omics data (metabolomics, proteomics, microbiome, etc.) development of predictive models and digital decision-support
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technology, nanoscience, photonics and future electronic systems - for technical and societal development. Our cross-disciplinary approach gives interesting collaborations in academy, industry and society, and
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collection in real-world settings as well as controlled user studies, alongside the development of new theoretical models of human-robot communication. The PhD candidate will be supervised by experts in
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to the development of a bio-based, sustainable society. In particular, we focus on microbial processes and enzymes acting on renewable biomass. The division has an extensive instrument platform for analytics
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the mechanical properties of conjugated polymers and on the development of spinning processes for the manufacture of conducting polymer fibers for wearable electronics. A summary of the research field can be found
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This project focuses on the development of quantum–classical modeling strategies for multiphase flow systems. The PhD topic is on exploring how emerging quantum computing methods can be integrated with classical