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platform. Initially, a black box deep learning approach will be implemented. However, due to the need for robustness, transparency, and explainability (e.g. for quality control across sectors), the research
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promotes sustainable economic growth and higher levels of technological innovation. It will benefit society and create a safer and smarter world by providing decent work for all. Furthermore, autonomous
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early ‘prodromal’ stages) is yet to be established in large community settings. This PhD project will examine the effectiveness of AI-based analysis of eye images in predicting cognitive/neurodegenerative
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emissions by increasing the use of post-consumer scrap in aluminium production. Your work will enable the creation of high-quality aluminium surfaces that meet the highest standards, all while contributing
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Professor, appointment-stream position. The research is management and analysis of eye movement data collected from an ongoing collaboration with the UPMC concussion lab. Duties include evaluation and
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structures. Experimental Characterisation: Validating the manufactured prototypes through a range of advanced materials characterisation techniques (e.g., spectroscopy, optical and scintillation performance
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quantum reference frames. The team is embedded within the Quantum Optics, Quantum Nanophysics, and Quantum Information group at the Faculty of Physics (University of Vienna), and is also affiliated with
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quantum reference frames. The team is embedded within the Quantum Optics, Quantum Nanophysics, and Quantum Information group at the Faculty of Physics (University of Vienna), and is also affiliated with
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energy efficiency. Surface treatments and engineered coatings will be explored to improve inter-material interfaces, reduce optical losses, and enhance detector robustness, critical factors to advance
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the appointment. The successful candidate will be based at the John A. Moran Eye Center in Salt Lake City, Utah. The largest city in the Intermountain West, Salt Lake City is renowned for its world class ski