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Field
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This self-funded PhD opportunity explores assured multi-sensor localisation in 6G terrestrial and non-terrestrial networks (TN–NTN), combining GNSS positioning, inertial systems, and vision-based
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to develop AI models for image reconstruction from data from our ultra-thin fibre-based spatial frequency domain imaging device (SFDI) and also from our custom-built photoplethysmography (PPG) sensor
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(SFDI) and also from our custom-built photoplethysmography (PPG) sensor. Applicant should have experience in time-series processing with appropriate AI models (recurrent networks, LSTM) and experience in
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quality monitoring system. Potential applications will initially focus on drinking water distribution networks. The main sources of water pollution are relatively well documented in the literature
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attracting highly qualified talent. We look for researchers from diverse academic backgrounds to contribute to our projects in areas such as: Network Security, Information Assurance, Model-driven Security
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a big plus: Relevant publications (and/or M.Sc. thesis) on the above-mentioned research topics Programming Microcontrollers and Interfacing Sensors Machine Learning Algorithms and Deep Neural Networks
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-Curie Doctoral Network “SPACER“. It will be carried out by one doctoral candidate at the University of Stuttgart, Institute of Smart Sensors (IIS), with PhD supervision by Prof. Jens Anders and co
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produced from the outset. On the other hand, the information created in event-based sensors is more meaningful from the very start. Similarly, in calculators based on spiking neural networks (SNNs
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in quantum clocks and sensors. The network offers international secondments, joint training events, and close interaction with an international cohort of doctoral fellows. The doctoral candidate will
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include: Applying controlled stress treatments Phenotyping stress responses with various sensors and gene expression studies in real-time PCR RNA sequencing and transcriptome analysis with corresponding