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Field
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signal processing AI/ML for communication systems Self-supervised ML, meta learning PHY/MAC optimization of wireless communication systems Robust, reliable, or explainable ML Experience with large-scale
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to develop AI-enabled, low-latency signal-processing algorithms for next-generation pixel detectors used in high-energy physics experiments. This position offers the opportunity to engage in cutting-edge
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reference letter Additional Qualifications: Work experience on field observations and data analysis, for data relevant to atmospheric composition change and climate: 1 point per month up to 60 points (max
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acquisition and processing of associated signals and data. Essential Qualifications: Candidates must hold a Ph.D.; have the ability to work independently within a team environment; and have excellent
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experimental nonlinear photonics, optical communications, optical sensing and signal processing, optical frequency combs, biophotonics, fibre lasers, and semiconductor lasers. AIPT hosts the UK Multidisciplinary
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. Visit us on LinkedIn and discover how you can become part of our community. You will be part of the larger Biomolecular Mass Spectrometry and Proteomics group . The group focuses on the use of mass
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communication, applied AI, or a related field. You have experience with machine learning and signal processing, and preferably knowledge of RF or wireless systems. You can work with experimental data (e.g
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are looking for a researcher who: Holds (or is about to obtain) a PhD in molecular biology, biochemistry, or biophysics. Fulfills the formal criteria outlined in paragraph 2, point 2.1.1 of the NCN regulations
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the DOE mission. By participating, individuals will join a community of highly-skilled scientists and engineers, and will be equipped with the knowledge, experience, and training to contribute
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11 Nov 2025 Job Information Organisation/Company UNIVERSIDAD PUBLICA DE NAVARRA Department Research Management Service Research Field Physics Engineering » Communication engineering Researcher