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); units such as onboard computers, mass memories, remote terminals and instrument control units*; digital and analogue signal processing electronics for payload/platform functions; front-end acquisition and
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/molecular screens/assays (e.g., live-cell imaging, bioluminescence assays, digital PCRs, NGS) and the translation of gained insights into the generation of novel cell lines and vector formats (e.g., synthetic
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for seizure detection. These algorithms will be implemented on a spiking neural network (SNN) processing unit deployed on FPGA and custom-designed chips with an integrated detection mechanism. Research area and
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research areas: Diagnostic Imaging, Digital Health, Personalised Therapy, Precision Diagnostics, and Sensory and Neural Technology. Our technologies and solutions are developed with the aim of benefiting
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for companies to develop new and innovative services and products which benefit people and create value for society. DTU Health Techs expertise spans from imaging and biosensor techniques, across digital health
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languages such as Python, MATLAB, or C++, and experience with machine learning frameworks (e.g., TensorFlow, PyTorch) preferred. Familiarity with medical imaging processing and reconstruction techniques