11 multiscale-multi-scale-composite Postdoctoral positions at Chalmers University of Technology
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fluids, flow-induced pattern formation in both simple and complex flows (e.g. flow instabilities, product defects), multiscale analysis, and the application of machine learning techniques. About the
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Chalmers University of Technology focused on the recycling of carbon fibre composites. The project aims to develop a novel method for recovering fibres using magnetic fields, with the goal of lowering
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collaboration with the Multiscale Inorganic Materials group, both part of the Division of Energy and Materials at Chalmers . The two groups together comprise nine senior researchers and 27 PhD students and
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Laboratory is addressing thermal management and advanced packaging, mainly by manipulating nanomaterials and compositions to reach maximum thermal, electrical or mechanical performance. The group has a long
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alignement between technological capabilities and business model configutation to sustain competitive advantage Business model innovation in the digital era – development, scaling, and transformation
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organic semiconductors, polymer blends, and composites. Our research advances new plastic materials for wearable electronics and energy technologies. Collaborations with other universities, research
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The Müller Research Group specializes in the physical chemistry and materials science of organic semiconductors, polymer blends, and composites, with a focus on creating innovative plastic materials
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with modern machine learning and AI technologies to effectively address large-scale problems. About the research project We are seeking a highly motivated Postdoc to join our group in developing
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-scale computational methods, and bioinformatics. The division is also expanding in the area of data science and machine learning. Our department continuously strives to be an attractive employer. Equality
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and calibration of reports from various sources. Collect and analyse large-scale cross-industry accident data using FRAM (Functional Resonance Analysis Method) within LLMs to identify human-, technical