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role Conduct research on data quality and long-term reliability in smart sensor systems for industrial monitoring Develop methods, models, and computational tools for sensor data validation, anomaly
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to apply these modelling techniques to support the development of novel experimental technologies and AI-assisted optical sensors. Supported by the Structured Photonics Research Group at the University
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of naturalistic behavior. The successful candidate will contribute to projects involving participants with implanted intracranial electrodes and wearable non-invasive sensors, with a focus on naturalistic behavior
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. You have experience in machine learning applied to sensors. LanguagesENGLISHLevelExcellent Research FieldEngineering » Electronic engineeringYears of Research Experience4 - 10 Additional Information
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multimodal data. Your responsibilities include: Developing and applying machine learning, deep learning, and LLM-based methods to multimodal clinical datasets e.g. EHR, imaging, omics, sensor data Designing
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-area ElectroAnalytical, under a work contract for a non-fixed term, aiming at the development of electroanalytical sensors for the early detection of E. amylovora in fruit trees. 2. Applicable
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. • Experience in assembling, adapting and maintaining experimental devices, sensors, chambers, field structures or other environmental monitoring equipment. • Good organizational skills, autonomy and problem
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the research center Sensible Things that Communicate (www.miun.se/stc ) and deals with sensor-based systems and services for use within the Internet of Things and artificial intelligence. Job description We
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to sectors such as Geographic Information Systems (GIS), mobility management, the Internet of Things (IoT), and industrial sensorization. Tasks will include: Definition of reusable models and components
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sensors, instruments, and data analytics for such applications. The position responsibilities also include giving periodic progress reports via slide decks and written documents, working as part of a multi