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-XRF, Raman, FTIR in reflection mode) to enable multimodal data fusion and automated material characterization. • Apply and further develop machine-learning and statistical models (e.g. PCA, SAM
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pre-trained machine learning model for assessing cell condition based on EIS data is available from previous Master Thesis and will be integrated into the system. Here you create change literature
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, you will be an active part of our "Simulation and Data Lab Applied Machine Learning". Within national and European projects, you will drive the development of cutting-edge Machine Learning applications
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Max Planck Institute for Dynamics of Complex Technical Systems, Magdeburg | Magdeburg, Sachsen Anhalt | Germany | about 15 hours ago
the microbial metabolism, with applications in metabolic engineering and bioprocess optimization. Your tasks For two interdisciplinary research projectsin the field of computer-aided metabolic engineering, we
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-driven (machine learning) and model-driven techniques. As part of the DFG research project “Progressive, Spatio-Temporal Consistent Inline Activity Reconstruction and Recognition,” a doctoral position is
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Your Job: Research and extract industrial and commercial buildings across Germany using open-source geospatial data (e.g. OpenStreetMap, CORINE Land Cover, Sentinel, etc) Apply machine learning/AI
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excellent degree (Master of Science or equivalent) in machine learning, mathematics, robot learning, or a related field (please attach the relevant certificates to your application) A solid theoretical
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modeling and computational workflows Knowledge about machine learning: statistics and deep learning Experience in data analysis, visualization and presentation Good programming skills in languages such as
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-party research funding are expected. We are particularly interested in a candidate in any field of economics who leverages state-of-the-art machine learning and causal inference methods to innovative
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academic assignments at the chair What we look for in you Completed master’s degree in computer science, transportation, or related engineering fields Solid background in generative AI, machine learning, and