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with expertise in digital signal processing methods, and machine learning methods for amplitude and phase noise characterization of optical frequency combs, recovery of dual-comb measurement signals and
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mass spectrometry and machine learning now allow us to unravel this “dark proteome.” This position aims to use state-of-the-art AI-guided proteomics and systems biology approaches to map protease
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experience with advanced signal processing concepts as well as digital filters is advantageous. Your workplace You will be working at the Division of Electronics and Computer Engineering (ELDA), which conducts
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an exceptional international team with expertise in all aspects of the project. Your tasks will include: • Preparation of different EO and in-situ datasets for training a machine learning model • Development of ML
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student will become part of a team at DTU with expertise in digital signal processing methods, and machine learning methods for amplitude and phase noise characterization of optical frequency combs
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. Fe, S) on CNT purity and structure. Evaluate CNTs as conductive additives in standard Li-ion battery electrodes. Apply AI/machine learning to optimise experimental design and growth parameters
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/ . The group has been working on mmWave radar sensors in different applications, including automotive, indoor sensing, in-cabin monitoring, occupancy sensing, drones, multi-copters, gesture recognition, smart
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. The project proposes an innovative approach to model sea ice dynamics from the ice floe scale to the basin scale, leveraging hybrid data assimilation and machine learning methods to shape a physically robust
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courses on advanced semiconductor technologies Design pathfinding PDKs as learning assets Interuniversity research programs across Europe 🔬 Nano IC-related PhD topics include: Machine-learning for epitaxy
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. Outdoor spaces, indoor areas and transport facilities connecting them can become formidable barriers for people with disabilities during a travel journey. The diverse needs of individuals with different