40 parallel-computing-numerical-methods positions at Chalmers University of Technology in Sweden
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(AIMLeNS) lab is a tight-knit team of computer scientists, chemists, physicists, and mathematicians working collaboratively. Our focus is on developing practical methods that blend traditional disciplines
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research group that views automation engineering as a key enabler for new methods and applications, driving and benefiting from the ongoing digitalization of society. Our research emphasizes social, economic
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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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-centred tools for upskilling and augmentation of future workforces. You will join an excellent, diverse, and international research team. We develop methods and human augmentation, including upskilling
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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
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properties. Advanced characterization methods and development of new techniques – We specialize in hyphenated rheological methods such as rheo-SAXS and rheo-DES, which are primarily applied to materials like
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ocean, and an urgent need to inform regulatory bodies about associated environmental risks. The work builds upon methods developed in our previous inter- and transdisciplinary work on shipwreck risk
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will do The course FFY091 is structured around students completing laboratory work, numerical home assignments, and an optional problem set. Based on feedback from previous years, the optional problem
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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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and written English Strong academic record with publications or clear potential for publishing in top-tier journals Advanced knowledge of one or more qualitative and/or quantitative research methods