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, incorporating their own ideas and experience in computer vision, machine learning, and related fields, to further visualization and interpretation of molecular images. Our research environment focuses
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in computer vision, machine learning, and related fields, to further visualization and interpretation of molecular images. Our research environment focuses on methodological development in cryo
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broad spectrum of fields, from core to applied computer sciences. Its vast scope also benefits our undergraduate and graduate programmes, and we now teach courses in several engineering programmes
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theory, and learning theory to design efficient and robust decentralized AI systems. As postdoc, you will principally carry out research. A certain amount of teaching may be part of your duties, up to a
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and automated floor-plan recognition, to fill data gaps and harmonise information from disparate sources. Learn more and watch our project video here: https://sb.chalmers.se/digital-material-inventories
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of formulating them, incorporating their own ideas and experience in computer vision, machine learning, and related fields, to further visualization and interpretation of molecular images. Our research environment
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Are you interested in developing machine learning algorithms that provably help us make better decisions? Join us as a post-doc in the Division of Data Science and AI, Department of Computer Science
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of working with motion capture, eye tracking, machine learning, or other advanced behavioral analyses or related research experiences. A consistently excellent academic track record is required, including
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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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together with Jendrik Seipp, Senior Associate Professor in Artificial Intelligence at LiU. The research projects for the advertised position will be in the areas of automated planning and machine learning