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Hybrid Crop Modelling Framework, integrating Process-Based Models (PBMs) with Machine Learning (ML) to enhance the accuracy and interpretability of crop yield forecasts, while evaluating key ecosystem
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of machine learning tools in cognitive and neurosciences. This is a fixed-term, three-year position. The salary is in accordance with the German public service salary scale (65 % E13 TV-L). The Embodied
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research and publications in one or more of the following areas: Item response modelling Modelling of process data (e.g., response times) for competence tests Application of machine learning methods in
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mining and machine learning Leibniz-IWT is a certified family-friendly research institute and actively pursues equality for all groups of people. We promote the professional development of women
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team and actively participate in the DIPONI project (“Digital Transformation in Polymer Processing: Interoperability and Machine Learning Solutions for Process Optimization and Sustainability
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of computer science or using computer vision methods Excellent knowledge of the development and implementation of methods in the field of digitization, artificial intelligence, machine learning and/or 2D/3D imaging and
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). Knowledge of Docker and machine learning is considered a plus. Knowledge of standard bioinformatics tools for analyzing and interpreting Next Generation Sequencing data. Excellent oral and written
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such as ecology, economy and social sciences. ZMT aims to use data science tools, including computer vision and deep learning, for the study of rapid changes in tropical coastal socioecological systems
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organised, accurate in their experimentation and adaptable to learning new techniques. Primaryresponsibilities Preparation and processing of animal histological samples, including organ embedding, cutting and
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machine learning/artificial intelligence methods in combination with complex network analysis tools to predict and model interactions between food and biological systems Further scientific development