125 web-programmer-developer "https:" "https:" "https:" "UCL" "UCL" positions at Aalborg University
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development of the Department’s educational programs. The candidate will be expected to collaborate with young and senior researchers on the new research program CEBE. This includes participation in relevant
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Environments within the general study programme Electrical and Electronic Engineering; as per March 1, 2026, or as soon as possible thereafter. The candidate will be based in Aalborg at the Automation and
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at the bachelor program Global Business Engineering and/or MSc. program Management Engineering. This includes knowledge on, e.g., various perspectives and theories that inform the financial evaluation
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industrial injection moulding using recycled plastics. Variability in material properties of recycled polymers poses significant challenges for consistent product quality. This project aims to develop adaptive
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. The stipend is within the DEIS group and supervised by Professor Kim Guldstrand Larsen. Within DEIS the group has developed the award-winning tool UPPAAL (www.uppaal.org) supporting modeling, validation
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within the field of energy efficiency and system design and will be part of developing the field of hydraulic drive networks, why experience and theoretical knowledge within this subject is essential. You
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such as wind turbine applications, heavy duty truck chargers, medium voltage hardware technology for megawatt marine applications. The hardware tasks include development of new solutions for megawatt
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the general study program. The PhD Stipend is open for appointment from 01.02.2026 or as soon as possible thereafter. The position is for 3 years, and the workplace is in Aalborg. Your work tasks You will be
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Mathematical modeling of Knee OsteoArthritis) funded by the Novo Nordisk Foundation under the Challenge Program on Mathematical Modeling of Health and Disease. The MathKOA research project Osteoarthritis (OA) is
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of Computer Science (CS) and Sustainability and Planning (PLAN). This position focuses on the machine learning methodology of the project, aiming to: Develop probabilistic spatio-temporal models that integrate