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dissemination activities, and carry out research activities. Qualifications To be considered for the position, you need a solid background in: natural sciences (mathematics and physics), demonstrated proficiency
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-specific software like IDA ICE incl. pool extension. Responsibilities and qualifications The required selection criteria include: Strong knowledge of building physics and HVAC system Competence in developing
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to support real-time machine learning tasks at the edge. Seen from a multiple layer point of view, i.e. choice of physical layer, data link, network, transport - layer. Explore the option of distributed
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, and you are eager to apply these skills to tackle challenges, this is your opportunity. Responsibilities and qualifications As part of the selection process, you will collaborate with your supervisors
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the electrochemical process that occurs in thin electrolyte layer. One PhD project will focus on understanding the change electrochemical migration mechanisms and its effects on short circuiting and functional issues
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the reuse process of the elements. Responsibilities and qualifications The project consists of three parts: Documenting the most environmentally responsible end-of-life strategy for insulated concrete wall
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towards the degradation of the quality of life in European societies. In that context, efficient physics-based sound modelling is a key enabler towards not only optimized and sustainable acoustic profiles
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the objective. The combination of AI and robotics greatly accelerates the slow chemical space exploration process, which opens the door to designing new types of materials by effectively exploring
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qualifications The PhD student shall perform research within the development of a multi-physics modelling framework for fatigue damage in corrosive environments. The overarching aim of the project is to (1) couple
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, Denmark Job Description We seek a motivated, curious, and outgoing PhD candidate with a solid background in optical communication, laser physics or nonlinear optics. Experience with machine learning