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pathology applications, including the assessment of kidney biopsies. The innovative application of machine learning in clinical settings creates a vibrant and inspiring research environment. You will be part
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health, and bioinformatics. You will apply advanced AI methods - from classical machine learning to large language models and agent-based AI - on large-scale healthcare datasets, including structured
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on topics such as leadership for academic staff, time management, handling stress, and an online learning platform with 100+ different courses; 7 weeks of birth leave (partner leave) with 100% salary; partly
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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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stress, and an online learning platform with 100+ different courses; 7 weeks of birth leave (partner leave) with 100% salary; partly paid parental leave; the possibility of setting up a workplace at home
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. The candidate will also collaborate with the Department of Computer Science at Kiel University and the remote sensing company EOMAP GmbH, employing state-of-the-art machine learning techniques to improve
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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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Offer Description Funding: 36 months, CIFRE (https://www.anrt.asso.fr/fr/le-dispositif-cifre-7844 ) Starting date: November / December 2025 Keywords: Physically informed machine learning, Industrial
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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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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