20 computer-science-programming-languages-"the"-"U" positions at Linköping University in Sweden
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will also teach (initially exclusively in English) and supervise students in various programs at the Faculty of Science and Engineering. The position will eventually include course development and course
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part of the national research program WASP. Wallenberg AI, Autonomous Systems and Software Program (WASP) is Sweden’s largest individual research program ever, a major national initiative for
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of European AI Factories in collaboration with RISE AB. The AI Factory Service Hub is operated as a project under the Horizon Europe framework program and will include up to 50 AI experts and other staff
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connection with your admission to the doctoral program, your employment as a PhD student is handled. More information about the doctoral studies at each faculty is available at Doctoral studies at Linköping
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Factories. The AI Factory Service Hub is operated as a project under the Horizon Europe framework program and will include up to 50 AI experts and other staff working close to academic and industrial users
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undergraduate and advanced levels, primarily in our engineering program in Construction Engineering and our master's program in Digitalized Construction. Course orientations where you may be involved include
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and advanced levels, primarily in our engineering program in Construction Engineering and our master's program in Digitalized Construction. Course orientations where you may be involved include
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administration. Read more at Energy Systems . The employment When taking up the post, you will be admitted to the program for doctoral studies. More information about the doctoral studies at each faculty is
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qualification in a relevant subject e.g. bioinformatics, computer science or similar At least two years’ experience of working in a research environment with bioinformatics, genomics and interpretation of big
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application! Work assignments Subject area: Computational studies of the influence of microstructural features on the structural integrity of metallic materials using machine learning Subject area description