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aims at addressing computational challenges associated with data acquisition and information extraction from complex sensors and sensor networks. Crucially, uncertainty management and quantification
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SNNs are typically fed with spiking data (e.g., streams of binary values), and the output of each layer remains spiking. They are particularly well suited for several new sensors, such as event-cameras
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postdoctoral researchers and PhD students, pursuing research in many aspects of field theory, string theory, and integrability (for more information, see https://www.hw.ac.uk/uk/schools/mathematical-computer
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optoelectronics or closely related field. Electro-optical characterisation and measurement of detectors are essential. General tasks will involve scientific research; analysis and interpretation of data; daily
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, photoelectron spectroscopy, two-dimensional spectroscopy. Practical experience with vacuum systems, including ultra-high vacuum systems. Experience of programming for data acquisition and analysis (preferably in
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interpretation of data; daily oversight of the activities of postgraduate and undergraduate project students in the laboratory; communication with other investigators involved in this collaborative project
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at Université Paris-Saclay (https://cvn.centralesupelec.fr/ ), Prof. Pock from the Institute of Computer Graphics and Vision at Graz University of Technology (ICG ), Prof. Thiran from the EPFL Signal Processing