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German Cancer Research Center in the Helmholtz Association (DKFZ) | Heidelberg, Baden W rttemberg | Germany | 2 months ago
Machine Learning Engineer – Language Models and Agentic AI for Scientific Imaging Reference number: 2026-0142 Your Tasks We are seeking a highly motivated individual to join an interdisciplinary team
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engineering, computer science or a comparable subject You have good experience in Python You have basic knowledge of the theory and methods in machine learning Good language skills in German and/or English What
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Constructor Technology, invites applications for a PhD position in machine learning for software engineering and formal methods, on the Constructor Fabric project. Constructor Fabric turns a company's informal
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interface of machine learning, deep learning, data science and applications in forest sciences. Together with the Director, you will further develop KIForst as a faculty-wide platform for methodological
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applications. Simulation environments offer a promising approach to address this challenge. By accurately modeling the underlying physics of assembly operations, it becomes possible to learn generalized
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In this position, you will join our Simulation and Data Lab for AI and Machine Learning for Remote Sensing . The lab advances interdisciplinary research and operational services by combining
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evaluate statistical and machine learning models - Publish results in peer-reviewed journals Desired Qualifications - Master’s degree in statistics, mathematics, data science, bioinformatics, physics
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international conferences to present your own work. Your Profile Masters degree with subsequent PhD in computer science (or a related field). Rich experience in devising machine learning models, methods, and
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: investigation of ontology-based metadata models for the machine-readable description of model structures, workflows and parameter dependencies, as well as a multi-agent architecture (LLMs, Retrieval-Augmented
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Cognitive Science, Medical Informatics, or a comparable quantitative discipline Proven hands-on experience working with LLMs, foundation models, multimodal AI systems, or related machine-learning technologies