40 computer-science-programming-languages-"The-University-of-Akureyri" positions at Linköping University
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application! We are looking for a PhD student in Computer Science formally based at the Department of Computer and Information Science (IDA) as part of the national research program WASP. Wallenberg AI
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writing and speech. A solid background in software tools and engineering, operating systems, compilers, concurrent programming and in programming distributed, parallel and heterogeneous computer systems is
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of full-time. Your qualifications You have graduated at the Master’s level in Molecular Biology, Computational Biology, Immunology, or a related field, or completed courses with a minimum of 240 credits
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courses in engineering, physics or chemistry. Alternatively, you have gained essentially corresponding knowledge in another way. Experience with Computational Fluid Dynamics (CFD) is a must, and knowledge
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is a sustainable future through materials science. Read more: https://wise-materials.org All early-stage researchers recruited into the WISE program will be a part of the WISE Research School
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The position We are looking for candidates in construction material science with the focus of developing green reinforced concrete. The research task of this position includes hybrid material design
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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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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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AI, Autonomous Systems and Software Program (WASP). As a PhD student, you devote most of your time to doctoral studies and the research projects of which you are part. Your work may also include
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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