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physical simulations and machine learning techniques, you will investigate the ability of surrogate models to determine large wind farms’ efficiency and wake characteristics, as well as the wake model
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count. Characterisation of amplifiers developed specifically for data distribution, and investigation of energy efficiency. The candidate should have a master’s degree, or similar, in physics, optical
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process flows. Fabricate these in the DTU Nanolab cleanroom. Characterize the transducers both electrically and acoustically. Build experimental setups. Publish your results in scientific journals
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the Management Science Division, the research ranges from mathematical-based optimization models to process-oriented management models and is used in basically every sector, such as transport, energy
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intake, physical activity, and well-being) analyzing data writing scientific papers participating in European meetings in the HealthyW8 project We expect that you have a background in life science, health
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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