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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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identification and machine learning. The key challenge is striking a balance between, on the one hand, modelling the physical, dynamic and nonlinear behavior of the components with sufficient physical accuracy
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trustworthy, we facilitate large-scale and reliable use of AI across different industries. Your work assignments You will work at the intersection of machine learning, cybersecurity, and privacy, developing
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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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Do you have a background in deep learning and computer vision? Are you independent, creative and eager to take initiatives? Do you enjoy working in an international research group and interacting
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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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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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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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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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Alfred-Wegener-Institut Helmholtz-Zentrum für Polar- und Meeresforschung | Bremerhaven, Bremen | Germany | about 2 months ago
this PhD, we propose to apply statistical computing combined with machine learning (ML) to the spectrophotometric data to derive high-resolution information on CDOM absorption and its origin. This will be