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contribute to the development of novel algorithms and methodologies that enhance the robustness and accuracy of acoustic measurements. We are looking for a highly motivated candidate, with a relevant MSc
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index and broad transparency region. You will be supervised by Associate Prof. Andrea Crovetto, and will work closely with LightTrap colleagues at DTU Compute and DTU Physics. It is very important that
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(e.g., based on physiological signals or direct inputs from occupants) and developing algorithms, including machine learning methods. The work will include statistical modelling, data-driven modelling
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Job Description Are you passionate about brain-computer interfaces (BCIs), neurorehabilitation, and intelligent assistive technologies? The Department of Health Technology (DTU Health Tech