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and workflows (e.g., Hugging face, Keras, Torch, etc) Research experience in conducting end-to-end experiments and academic writing. Experience writing Python programs and using developer tools (e.g
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a robust predictive framework that enables precise prediction of reaction outcomes. The project is part of an international collaboration with the German Priority Program on the “Utilization and
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. The focus is on developing AI-supported, sensor-based solutions for real-time monitoring and optimization of manufacturing processes. These solutions aim to assess process conditions during production
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the “Basisprüfung” or its equivalent with good grades. MSc students and BSc students in the fifth semester or higher are preferred, although students earlier in their program will be considered if their grades
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, students, and external partners to develop innovative teaching approaches, foster interdisciplinary collaboration, and facilitate knowledge transfer across degree programmes. The position is limited until
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research in mineralogy, dynamics, and evolution of deep planetary interiors. Project background The Experimental Mineral Physics group applies high-pressure and high-temperature experimental approach mainly
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offered by the ASVZ , childcare and attractive pension benefits . Training opportunities Perspectives for career development Support programmes (e.g., mentoring) and networks Fruitful working environment
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We are seeking a highly motivated and interdisciplinary Postdoctoral Researcher to join our team in developing a cutting-edge nutrient prediction platform. This project integrates machine learning
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Our research group focuses on the development of AI algorithms for industrial applications. The main scope of our activities is the optimization and automation of workflows and production systems
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through the development of strategies for long-term data quality improvement and data curation, including persistent identifiers for organizations, researchers and funding Supporting the writing of reports