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selectivity is the first important barrier to overcome in order to perform quantitative analyses for each pollutant and avoid ionic interference between the different sensors used in the project. Sensor
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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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years, with a focus on creating an inclusive and bottom-up driven research environment. Our workplace consists of a diverse set of people from different nationalities, backgrounds and fields. As a PhD
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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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to have good knowledge of computer science, mathematics, algorithms, and programming. Knowledge and experience in artificial intelligence and machine learning is expected, but not required. Knowledge and
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advantages. We will provide the necessary hardware and software for the real-time control of the machine, but the candidate will be responsible for developing and implementing the control algorithms. A working
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reliable and reproducible measurements across different assays. In this PhD project, you will develop RMPs and reference materials (RMs) for several protein TMs to enable harmonized and reproducible
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. Knowledge Graphs based on engine propeller combinator diagrams of the same vessels. Machine learning algorithms for data clustering and regressions of ship performance and navigation data sets as a part of
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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