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system requires effective orchestration that can schedule the application on these systems. While traditional scheduling algorithms exist, these do not focus on the energy footprint of applications
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. Because of the specific structure of the inference problems occurring in metabolic models, direct application of these MCMC algorithms is, however, not possible. In this project, you will bring MCMC methods
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methods, machine learning algorithms, and prototypical systems controlling complex energy systems like buildings, electricity distribution grids and thermal systems for a sustainable future. These systems
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AI and machine learning algorithms? Then you've come to the right place. Excellent programming skills (preferably in Python) are required. A strong interest in interdisciplinary work at the
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. Therefore, we employ a broad range of artificial intelligence algorithms that enrich process data with sophisticated domain knowledge and semi-supervised approaches to incorporate unlabeled data. We
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processing workflows including QC and reproducibility metrics * APIs and packages supporting the development of new algorithms spanning large * language modeling of DNA and RNA sequences, and algorithms
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to the road? Then this position is just right for you! About us In the Autonomous Vehicle Lab, we develop the vehicle of the future with intelligent algorithms and methods. We are involved in numerous projects
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, but also in traffic monitoring or in the media context, for example when it comes to automatic metadata extraction and audio manipulation detection. Another focus is the development of algorithms
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energy use more efficient. We develop new optimization methods, machine learning algorithms, and prototypical systems controlling complex energy systems like electric grids and thermal systems for a
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(https://www.icos-cp.eu/projects/icos-cities ) Design and implementation of suitable algorithms, using the High Performance Computing infrastructure at Leibniz Rechenzentrum (LRZ) Analysis of ground-based