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Field
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the primary responsibility of performing metallomics studies including the preparation of responsive fluorescent sensors for application in biological studies. This project is funded by a grant from the Human
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trustworthy medical AI? Deep models already outperform humans on many benchmarks, yet in the clinic they remain black boxes: radiologists cannot see why an algorithm flags a lesion, and AI engineers cannot tell
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across AI, incorporating insights from algorithm development, systems engineering and architecture, human psychology, sociology, law, science and technology studies, economics, and policy studies. Faculty
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across AI, incorporating insights from algorithm development, systems engineering and architecture, human psychology, sociology, law, science and technology studies, economics, and policy studies. Faculty
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- conducting processors with respect to practical short-depth (NISQ) quantum algorithms Cooperate and actively work with experimental partners developing quantum processors using these technological platforms
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vision, IoT sensors, and blockchain to monitor food quality, safety and animal welfare in real-time and enhance transparency. AI and machine learning will analyse data from pilot sites to identify
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(LiB’s). You will be responsible for: • Developing models and simulations of the electrode fabrication process, sensors, and actuators. • Developing a demonstrator of a soft sensing system that
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the field of analytical and/or simulation methods for composite materials. You have extensive experience with development and implementation of algorithms for modelling of composites You have experience with
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, physics, or a medical imaging related field. Experience with developing advanced pulse sequences or accelerated acquisition and reconstruction algorithms will be highly valued. Interested candidates should
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Spectroscopy (dwSCOS) sensor for non-invasive microvascular monitoring. 2. Perform Monte Carlo simulations for optical modeling of photon propagation in layered tissues. 3. Fabricate and characterize dynamic