60 systems-science "https:" "https:" "https:" "https:" "I.E" "UCL" positions at Linköping University
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economics and management to technology and design. The department is characterized by a strong focus on renewal, development, and innovation as means to contribute to a sustainable society. Many PhD graduates
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technologies. The OEM group is part of the Laboratory of Organic Electronics (LOE) (https://liu.se/LOE ), an internationally renowned research environment comprising more than 150 researchers from diverse
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priority research areas. Since 2008 REMESO’s PhD education is integrated with an international Graduate School in Migration, Ethnicity and Society. More about the REMESO research environment here https
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, statistics, machine learning, control, computer science, or a related area that is considered relevant for the research topic of the project, or have completed courses with a minimum of 240 credits, at least
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Genomics core facility which is jointly run by the division of cell and neurobiology, CNB, at the Department of Biomedical and Clinical Sciences (BKV ) and the Medical Faculty. Find more information about us
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skills in English. Oral and written communication skills in Swedish is a merit. You have graduated at Master’s level in computer science or completed courses with a minimum of 240 credits, at least 60 of
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employed in the Cybersecurity division with close to 50 members at the department of Computer and Information Science (IDA) . You will carry out research together with Simin Nadjm-Tehrani, Professor in
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conduct research on the theoretical foundations of mathematical optimization, as well as its applications to emerging challenges in machine learning and engineering. You will write and submit research
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at the Department of Electrical Engineering. The Division of Communication Systems conducts research and education in communications engineering, statistical signal processing, network science, and decentralized
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application! Your work assignments We are looking for a PhD student to work on the development of novel spatio-temporal machine learning methods. Our world is inherently spatio-temporal, i.e. physical processes