447 machine-learning-"https:"-"https:"-"https:"-"https:"-"https:"-"Ulster-University" positions in Germany
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- cellumation GmbH
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Learning, especially in spatiotemporal modelling, environmental data analysis, or multimodal learning, Practical experience in applying Machine Learning, ideally including deep learning, foundation models
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based on our own machine learning models and it supports research in our field. The system consists of a multi-node environment, with an Elasticsearch database, data pipelines in Go and Python Data is
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Nancy and the long-standing experience in sophisticated computer simulation studies from Leipzig, promising unique prospects in advanced education of PhD students via research into this important field
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: active learning (uncertain cases first), smart sampling, confidence thresholds, gradations (auto-label/review/manual), measurement and decision logic for throughput vs. quality. Proficiency in programming
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, Süddeutsche Zeitung). Learn more about our research at www.erturk-lab.com . We are seeking a highly motivated AI Scientist (best: Computational Pathologist / Machine Learning Scientist for Digital Pathology) (f
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training machine learning models (ideally with a focus on LLM), high-performance computing, data management, and software architecture Strong Python programming skills and familiarity with machine learning
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societal actors, including scientists, local administration, coastal communities, and other decision-makers apply skills in data science, advanced AI interface development and machine learning to apply
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international conferences. This can provide opportunities for networking and learning from other researchers in your field. Extracurricular Seminars and Trainings The in-house umbrella organisation INGENIUM
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packages for machine learning. You are not afraid of learning new technologies and frameworks. You enjoy developing prototypes. You are independent, creative and curious and you can work independently. What
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, imaging). • Solid foundations in signal processing and statistics. • Experience with machine learning for regression (e.g., tree-based methods, neural networks) • Hands-on experimental skills: ability and