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and Mechanical Engineering (DTU Construct). In this role, you are advancing innovation by integrating material science, advanced processing techniques, and modelling to gain a comprehensive
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-based simulation model for assessing future mobility technologies in the Greater Copenhagen region. Explore the development of machine-learning based scenario discovery for future mobility policy design
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structures i.e. in aircrafts, containing adhesive and disband damages. The research activities will initially include one or more of the following areas: Advanced finite element modelling of disband damaged
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(RAG) models – are shaping professional expertise and practice across diverse Danish public sector domains, especially among frontline workers, including caseworkers, service providers and welfare
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engineering, nutrition science, and data-driven modeling to develop healthier and more sustainable food systems. We seek a highly motivated and innovative individual to join our team and collaborate closely
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for optimizing the energy consumption, mathematical models for digital twin technology, and minimum interoperability mechanisms for streamlining the integration across devices, consumers, and technologies. You
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with colleagues at DTU and IIT Bombay, as well as with academic and industrial partners globally. The main purpose of this PhD position is to develop, implement and assess machine learning models
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College Dublin, Ireland and Northeastern University, USA. Responsibilities The PhD project involves developing a flexible vegetation model within the OpenFOAM platform, where vegetation stems
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this area. We have excellent facilities and competences for fabrication, modeling, testing and characterization of associated materials and devices. Responsibilities and qualifications The focus