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learning algorithms, and design of optical communication networks or power consumption and energy saving. The synergies of MATCH consortium act together to enable the thirteen DCs to become the next
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this data. Clustering travel needs. To define different mobility needs and motivations based on the travel data, we apply different clustering algorithms (e.g., traditional k-means, density-based clustering
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collaboration with the Intelligent Maintenance and Operations Systems (IMOS) Laboratory at EPFL (Prof. Olga Fink). IMOS focuses on the development of intelligent algorithms designed to improve the performance
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Alfred-Wegener-Institut Helmholtz-Zentrum für Polar- und Meeresforschung | Bremen, Bremen | Germany | 3 months ago
functions to detect ecosystem change and predict ecosystem characteristics under different impact scenarios. The integrated analysis of marine microbial eDNA data and contextual environmental information with
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to work independently as well as in teams Work in a structured way, set goals and make plans to achieve them, result-oriented Excellent analytical skills, analyze data, assess different perspectives and
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involved, leads to complex logistics problems. The planning of rolling stock circulations and the regular maintenance at the various service locations is typically done by different planners. In addition
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algorithms to compute similarity between interaction interfaces across millions of comparisons. This hinders identification of novel modes of protein binding, i.e. those predicted by AlphaFold, and it hinders
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experimental testing. You’ll design and run experiments, write and train algorithms, and contribute to open-source tools that may one day become industry standards. This project offers the freedom to explore
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normalization and integration of data from different sources, defining appropriate strategies to deal with all ethical and privacy/security requirements; Contribute to the development, validation and integration
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is not a standalone concept and has close connections to diversity, transparency and bias. In this position, the PhD candidate will work on algorithmic fairness in job recommender systems