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of the department's modern laboratory-, core- and animal facilities. The Department of Biomedicine focuses on innovation, entrepreneurship and collaboration with business and industry, and numerous researchers from
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doctoral candidate who meets the following requirements: A background and strong interest in aluminum alloys, fatigue analysis, and numerical modelling is preferred. Experience with computer aided design
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theoretical and computational work in topological photonics and nanophotonics. Day-to-day project activities will include numerical computation and theoretical analysis of the photonic properties of candidate
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opportunity to be part of large-scale experiments tackling pressing societal challenges. You'll be involved in every stage of the research process—from experimental design to data analysis and publication—while
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in machine learning and artificial intelligence Experience with numerical analysis and scientific computing Knowledge of power systems and renewable energy technologies Experience in power system
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design to testing, programming neural interfaces, neural data analysis. We offer DTU is a leading technical university globally recognized for the excellence of its research, education, innovation and
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recognised track records. CNAP participates in numerous international initiatives and maintains an extensive global network, making it an ideal environment to build your own collaborative connections. CNAP is
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-driven methods for structural analysis under multiphysics loading”. Expected start date and duration of employment This is a 4–year position from September 1st, 2025, or as soon possible. Job description
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learning Control theory Experimental design and data analysis Simulation Furthermore, the successful candidate is expected to: Have excellent knowledge of English (written and spoken). Be able to work well
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experience with: Signal processing Experimental design and data analysis Furthermore, the successful candidate is expected to: Have excellent knowledge of English (written and spoken). Have high self