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to retrieve geophysical information from satellite data. Our research drives innovation in instrumentation and retrieval algorithms, and tackle climate change, air pollution, natural hazards, and land/ocean
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computational costs by orders of magnitude and enabling breakthroughs in drug design and materials science. The position bridges machine learning and molecular science, with opportunities for collaboration
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vulnerabilities and proposing effective defenses, the project seeks to make the next generation of the Internet more secure, resilient, and trustworthy. About us The Department of Computer Science and Engineering
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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
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Are you passionate about sustainable biotechnology and ready to tackle one of today’s biggest environmental challenges? Join our dynamic and interdisciplinary team at Chalmers University of Technology to pioneer the next generation of biorefineries using marine and terrestrial biomass. This...
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modular, scalable, and transparent control algorithms suitable for real-time implementation across different vehicle platforms. - Contribute to theoretical developments in stochastic model predictive
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to individuals who are currently enrolled in a master’s program at Chalmers University of Technology. Essential personal attributes include curiosity, persistence, and a learning eagerness. In addition, valuable
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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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activities, which also include responsibility for the master's programme in Naval Architecture and Ocean Engineering and contributions to the education of seafarers. Your profile To qualify for this position
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to develop solutions with real world relevance and impact. This project will be carried out in close collaboration with researchers from the Division of Material and Computational Mechanics at IMS and the