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to demonstrate documented proficiency in English. You have knowledge and expertise in computer vision and/or medical image analysis, deep learning as well as mathematics. You have substantial expertise in
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engineering (focusing on deep learning for computer vision), and the division of statistics and machine learning at the department of computer and information science (focusing on the theory behind machine
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class sessions, assisting teachers in class sessions and laborations, assisting teachers at seminars and marking exams in Quality Management and Engineering courses. Work may also include lighter forms
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NAISS, the National Academic Infrastructure for Supercomputing in Sweden, provides academic users with high-performance computing resources, storage capacity, and data services. NAISS is hosted by
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, experience and expertise are required: A PhD or equivalent e.g. a master’s degree with several years of working experience in natural sciences, computational sciences, engineering or mathematics. Experience in
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Science, Computational Science and Engineering or completed courses with a minimum of 240 credits, at least 60 of which must be in advanced courses in which you have gained expertise in applied mathematics
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different backgrounds. This position requires that you have graduated at Master’s level in in computer science, media technology, computer engineering, human-computer interaction, visual learning and
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for the position: An established and active research program in Neuroengineering. Deployment of engineering-based methods for development and analysis. Experience of research conducted in close collaboration with
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application! We are looking for a research engineer within the Division of Statistics and Machine Learning (STIMA) at the Department of Computer and Information Science. In this position, you will have the
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Institute of Technology, Chalmers University of Technology, and Linköping University. The center is based on the vision that the forest can provide sustainable bio-based alternatives to today’s fossil-based