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the division of Data Science and AI , we develop data-driven methods and AI solutions that support intelligent decisions across society, advancing machine learning techniques, from foundations to industrial and
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the division of Data Science and AI , we develop data-driven methods and AI solutions that support intelligent decisions across society, advancing machine learning techniques, from foundations to industrial and
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of AI-driven electric transport systems? Join our research group to develop advanced machine learning methods for electromobility, focusing on energy-aware coordination of electric vehicle fleets
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Do you want to contribute to the future of AI-driven electric transport systems? Join our research group to develop advanced machine learning methods for electromobility, focusing on energy-aware
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analyses. The postdoc will be hosted at TDB, co-supervised by both groups, and will work at the interface of scientific computing, machine learning and particle physics. Project description Searches for dark
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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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intelligent decisions across society, advancing machine learning techniques, from foundations to industrial and scientific applications. About the research project You will work in Julian Togelius' new research
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equivalent foreign degree, obtained within the last three years prior to the application deadline Experience with simulation frameworks, system-level performance evaluation, or machine learning, is highly
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. The postdoctoral researcher(s) will join an international research environment at Umeå University, including Stat4Reg (www.stat4reg.se ), which develops statistical and machine-learning methods for register data
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-driven approach for optimizing the growth of semiconductor materials by combining machine learning with a physics-based understanding of the growth process. Doping and processing of ultra-wide bandgap