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acoustic imaging, artificial Intelligence and signal processing. They will develop skills in both modeling and experimentation. Location and Environment: The student will conduct their research
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multi-channel signal generators, amplifiers, and a wide range transducers and arrays. Additionally, a high-performance computer cluster is available at Bristol can be used to run large and parallel models
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of trees using AI methods on acoustic signals All details here: https://www.eu4greenfielddata.eu/content/download/201/2097?version=3 Context: Abiotic stresses (e.g. frost, drought, wind) cause significant
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SPEAR Centre: PhD in ‘Long-Range, High Bandwidth Distributed Acoustic Sensing for Fibre Optic Links’
Programme? Other EU programme Is the Job related to staff position within a Research Infrastructure? No Offer Description SPEAR Centre: PhD in ‘Long-Range, High Bandwidth Distributed Acoustic Sensing
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artificial intelligence techniques in the context of physical modelling. Proficiency in signal and data processing, including time- and frequency-domain analysis. Familiarity with instrumentation for non
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behavior and/or brain physiology. A strong analytic background, particularly in modeling neural systems and analyzing large datasets. Experience with acoustic signal processing, sound recognition, and
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of target species, and 2) identify and map the risk of interactions between sea turtles and fishing gear. Main tasks: - Processing accelerometric/gyroscopic and acoustic signals related to the fine behaviors
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imaging. Key Responsibilities: Design and carry out ultrasonic experiments and develop signal processing techniques Develop theories of acoustic wave propagation in complex materials Design numerical
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intelligent sensors and robotics that revolutionize how we diagnose, monitor, and treat a wide range of diseases. The Postdoctoral Researcher will play a key role in the co-development of advanced acoustic
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understanding of how acoustic waves are generated and transmitted in wells. The LeDAS project aims to overcome these challenges by combining physical modelling, advanced signal processing, and machine learning in