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future. Fueled by curiosity and a deep sense of duty, they contribute invaluable insights to research and teaching, enriching our society. Are you inspired and driven by the desire to make a meaningful
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characteristics of TMEs [1]. In lung cancer, several deep learning studies using Haematoxylin and Eosin (H&E) images have demonstrated that the spatial organisation of stromal and immune cell populations within
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of novel probabilistic deep-learning models that automatically extract mechanistic and statistical knowledge from your in vivo perturbational omics data. This interdisciplinary atmosphere has been a main
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SPECIFICS Postdoctoral Scholar – Public Health Sciences Postdoctoral Scholar of Machine Learning and Statistical Genomics Description: The Department of Public Health Sciences is seeking postdoc scholars
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control framework for microfluidic live-cell analytics in close collaboration with partners at HZI, Helmholtz Munich and HHU. Your tasks in detail: Establish deep-learning–based segmentation, species
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(“overparameterized”) machine learning models, like probabilistic graphical models, deep neural networks, diffusion models, transformers, e.g. large language models, etc. SLT is based on the geometrical understanding
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at Forschungszentrum Jülich, in close collaboration with bioimage analysis partners at Karlsruhe Institute of Technology. Your tasks in detail: Develop and extend deep-learning–based segmentation, classification and
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7,500 academic staff members, who passionately pursue answers to the profound questions that shape our future. Fueled by curiosity and a deep sense of duty, they contribute invaluable insights to research
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, etc.). Robust AI (knowledge of methods for quantifying uncertainty in deep learning or formal verification methods applied to deep learning) Embedded AI Reinforcement learning, supervised and
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of over 10,000 individuals, including approximately 7,500 academic staff members, who passionately pursue answers to the profound questions that shape our future. Fueled by curiosity and a deep sense