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, computer science, machine learning, or natural language processing, focusing on AI for Social Good or similar. Excellent written and spoken English is required, since the project is carried out in an international
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Description Job description Game theory is rapidly gaining traction in several engineering applications as the natural framework for multi-agent decision making. Yet, unlike optimization, game theory has
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technology and natural sciences at a high international level. The university has 3100 employees and 10,000 students, and offers education in engineering, science, shipping and architecture. With scientific
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the recruiting process in connection with this position. *** Chalmers University of Technology in Gothenburg conducts research and education in technology and natural sciences at a high international level. The
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. Application procedure The application should be written in English be attached as PDF-files, as below. Maximum size for each file is 40 MB. Please note that the system does not support Zip files. CV A
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language, Chalmers offers Swedish courses to help you settle in. Application procedure The application should be written in English be attached as PDF-files, as below. Maximum size for each file is 40 MB
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language, Chalmers offers Swedish courses to help you settle in. Application procedure The application should be written in English be attached as PDF-files, as below. Maximum size for each file is 40 MB
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inclusion as fundamental aspects of all our activities. If Swedish is not your native language, Chalmers offers Swedish courses to help you settle in. Application procedure The application should be written
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Worldwide R&D Projects. Previous experience in one or preferably more topics from these areas is considered a merit: - Multi-modal data processing for decision-making in natural environments - Terrain
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-facing web GIS dashboard. Investigate the forest, landscape, and climate conditions that drive storm susceptibility, using major windstorms as natural experiments and interpretable machine-/deep-learning