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The SnT is seeking a Postdoc to support the research and development work within the SEDAN group. We seek a candidate with expertise and/or interest in the following relevant fields: machine
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use tools such as artificial intelligence/machine learning, graph theory and graph-signal processing, and convex/non-convex optimization. Furthermore, our activities are experimentally driven and
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interest in the following relevant fields: machine learning and cybersecurity. While robust infrastructures now exist for running cybersecurity exercises, the creation and management of training scenarios
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and optimization, we use tools such as artificial intelligence/machine learning, quantum conputing, graph theory, graph-signal processing, and convex/non-convex optimization. Furthermore, our activities
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publish in top-tier Computer Vision and Machine Learning conferences? Do you have extensive experience working with industry on applied projects? Are you a passionate leader with a people-oriented approach
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, machine learning, data visualization, digital hermeneutics; an interest in media history or history of technology would be an asset Fluency in English and good knowledge of French or German Ability to work
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, neurosymbolic methods, or other emerging directions within machine learning. We particularly value depth of knowledge, originality, and the potential for cross-disciplinary innovation. Relevant application areas
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technologies, biophysics, soft and living matter, photovoltaics, spectroscopy, and machine learning. DPhyMS fosters a collaborative spirit through partnerships with all faculties at Uni.lu, national research
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of metabolic network modelling linked to epigenetics Carry out machine learning, and integrative analysis of large epigenome datasets Communicate research results in international conferences and journals Work
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driving, in-car monitoring, industrial automation, and security surveillance. The research, called "R4DAR," aims to leverage emerging 4D imaging technology with Massive MIMO to create image-like radar