656 machine-learning "https:" "https:" "https:" "https:" "RAEGE Az" uni jobs in Germany
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compiling information on a current topic in the field of machine learning. Researching and implementing novel machine learning and computer vision approaches. Self-critical evaluation of the obtained results
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their thesis under our supervision. This project builds upon our prior work in Multi Agent Reinforcement Learning (MARL) for real-world use-case of aerial ad hoc networks (see our paper ) and aims to advance
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classification systems (RISE, GradCAM, EigenCAM, Integrated Gradients, ViT Shapley, etc.) Implementation and execution of experiments in the field of machine learning (ML): Cleaning, preparing, splitting
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University Medical Center of the Johannes Gutenberg University Mainz | Mainz, Rheinland Pfalz | Germany | 2 months ago
), is offering a fully funded PhD position in the area of statistical learning, machine learning, and survival analysis applied to large-scale proteomics and multi-omics cohort data. The PhD project
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-depleting strategies on the lymphatic tissue Annals of the Rheumatic Diseases, 2025 https://doi.org/10.1016/j.ard.2025.06.2120 CD19-CAR T-cell therapy induces deep tissue depletion of B cells Annals
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-friendly frameworks for multimodal elastography and enabling deployment on portable devices (e.g., smartphones) for real-time diagnostics. The research combines continuum mechanics, machine learning
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adapters should be created and tested for previously selected detection methods, which can reliably bypass these detection methods. Be part of change Researching and implementing novel machine learning
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following areas: Strong foundation in machine learning, optimization, and deep learning algorithms, including Transformer architectures. Hands-on experience or solid theoretical knowledge of LLMs/SLMs
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sciences You are organized, reliable, and proactive You are a good communicator and enjoy teamwork You are comfortable working in English ((at least B2 level according to the CEFR: https://go.fzj.de
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28.05.2025, Academic staff We are looking for talented and ambitious scientists interested in unique interdisciplinary research, integrating machine learning, molecular simulations, statistical