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Field
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of electron spin pairs in chiral molecules created by light using diamond-based quantum sensors. Spin dynamics of these radical pairs are central both in biology and for quantum information science applications
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—remains a critical challenge. This project will focus on designing AI-driven cognitive navigation solutions that can adaptively fuse multiple sensor sources under uncertainty, enabling safe and efficient
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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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and sensor fabrication, host of precision electrical/optical/biochemical characterisation techniques, simulations and first principles theoretical calculations of these advanced materials. In addition
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welfare are monitored on farms. However, many current monitoring systems rely primarily on visual or activity-based sensors, meaning important behavioural and physiological signals may be missed. Sound
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images, XCT scans, time-series from sensors during AM and/or vector/scalar datasets like XRD), with an initial focus on identification and deployment of techniques for proper data fusion/transformation
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project, we are looking for a talented PhD candidate that can establish novel processes for fabrication of 3D pyrolytic carbon nano- and microelectrodes and integrate them into sensor platforms
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functionalisation strategies, and cutting-edge characterisation techniques (including Manchester Met’s unique in-situ electrochemical-AFM-nanoRaman (TERS) system) to optimise sensor performance. The research will
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field assets: experience with camera traps/sensor networks, interest in biodiversity, and a valid EU driving license How to apply The call for applications remains open until the position is filled
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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