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of context-aware, distributed, and embedded cyber-physical systems, with a particular focus on Internet-of-Things (IoT) and the computing continuum eras. Our vision is to pioneer advancements in high-tech
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for the position. Embedded Systems Engineering (ESE) is one of the 10 research sections at DTU Compute. Our mission encompasses the creation of insights that allow the development of context-aware, distributed
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on robotics, biomedical sensor and AI algorithm for cancer diagnosis. This project aims to develop a miniaturized robot and bio-sensor for on-site laryngeal cancer diagnosis. The candidate can contribute to one
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mechanism. Recent developments in protein structure prediction and protein de novo design have opened new possibilities for probing such mechanisms. The project will seek to use existing algorithms to new
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microstructural engineering will focus on in-situ optimization of the local distribution of grain sizes, crystallographic orientations, and stresses by the novel possibility of varying the laser beam shape and spot
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implementing inversion algorithms, including a focus on the integration of spatially constrained regularization schemes. Collaborating with forward modeling experts to ensure seamless integration with a recently
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of context-aware, distributed, and embedded cyber-physical systems, with a particular focus on Internet-of-Things (IoT) and the computing continuum eras. Our vision is to pioneer advancements in high-tech
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contributing to specifically the area of handling spatial data to assess the distribution of several soil properties and fungal communities using samples collected from multiple habitats and land use types at a
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the development of context-aware, distributed, and embedded cyber-physical systems, with a particular focus on Internet-of-Things (IoT) and the computing continuum eras. Our vision is to pioneer advancements in
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soil microbial communities. You will be contributing to specifically the area of handling microbial data to assess the spatial distribution of several soil properties and fungal communities using samples