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demonstrating machine polishing processes of complex mould surfaces using compliant polishing tools by implementation of sensing solutions enabling process, tool and surface condition monitoring. The goal is to
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thus including sensing systems, tool condition features selection, algorithms for automated signal preprocessing, feature extraction and decision making based on ML and AI. An integral part of
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Electro in the Quantum and Nanophotonics Section , which focuses on leveraging fundamental light-matter interactions for applications in sensing, optical communications, and quantum technologies
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proficient in ROS/ROS2, Python and/or C++/C# Knowledge and/or experience within one or more of the fields of acoustic sensing, hydrodynamics, and machine learning is a plus. You have strong communication
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Communication, Singal Processing, Low Power Electronics, Wireless Sensing, Low-Power System Design, Machine Learning & Edge Inference, Underwater acoustic communication. Furthermore, you have a proven record of
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including PhD students and postdocs. Also, a good sense of humor will be appreciated. Good English language skills will be required. The main criterion for selection will be the research potential
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activities in relation to food technology, food chemistry, and food nutrition in a broad sense. Teaching activities will include supervision of student projects at different levels (BSc, MSc, PhD). You will
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MSc degree (or equivalent) in oceanography, including components of ocean science and engineering Experience in ocean observation technology including remote sensing, in-situ observations and data
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traditional embedded systems fields, such as networked embedded systems, distributed sensing systems, mobile and wearable systems, ubiquitous systems, and the (Industrial) Internet of Things. Candidates who
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part of the Drug Delivery and Sensing (IDUN) section at DTU Department of Health Technology. Furthermore, the PhD project is in close collaboration with the adjuvant research team at The Department