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Field
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with researchers at DTU and KTH, you will help develop an integrated decision-support system that: Uses real-time sensor data and AI models to assess risk scenarios. Dynamically recommends optimal
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, modelling and simulation of photonic systems, sensor systems, signal processing and device manufacturing, development of machine learning algorithms, and design of optical communication networks or power
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their glial niche. Genetically encoded, fluorescent metabolite sensors will be used to study the underlying metabolite dynamics. The work will also incorporate various molecular biology techniques, as
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their glial niche. Genetically encoded, fluorescent metabolite sensors will be used to study the underlying metabolite dynamics. The work will also incorporate various molecular biology techniques, as
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the University of Montpellier and the CNRS. It specializes in the study of sensors, components, and systems 2 intended for hostile environments. The primary objective of the IES is to design and develop innovative
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Current reseach is in the areas of: Development of biomimetic structures as ultrasound contrast agents Deep tissue imaging using photoacoustic contrast agents All optical photoacoustic sensors
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from manufacturing sensors and XR headsets (video, audio, motion). This includes building multimodal AI pipelines, generating procedural representations, and contributing to the integration of real-time
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qualification (usually PhD). Tasks: The aim of the project is to design, model, fabricate and test a wireless micro-sensor which uses magnetic fields for sensing in biological soft tissues. For further
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engineering, clinical research, and AI-driven health monitoring. This project will explore large-scale maternal datasets—combining clinical cardiovascular assessments with wearable sensor data—to detect early
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off-the-shelf sensors and the development of resilient algorithms that combine first-principles modeling with modern machine learning techniques. The goal is to push the boundaries of robust perception