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. These projects span topics including the relationship between food production, environmental impact, and human health, as well as developments in agricultural robotics and automation. This environment offers broad
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with scientific programming and quantitative data analysis, particularly in Python, is welcomed. Experience with droplet generation, thermal diagnostics, image processing, or automated experimental
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. These projects span topics including the relationship between food production, environmental impact, and human health, as well as developments in agricultural robotics and automation. This environment offers broad
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( STAR ) and the Automated Design of Algorithms ( ADA ) research groups. Moreover, there are plenty of opportunities for interaction and collaboration with other groups at the institute and internationally
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worldwide. Your work will include: Apply existing machine learning algorithms for automated detection of CO plumes in satellite observations Building a global catalogue of CO emission events from 2018 onwards
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the goal to obtain more in-depth process understanding and develop automated control strategies for single cell microbial suspension cultures. Currently, the team is working on liquid- and gas-phase
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include AI-assisted signal analysis, transformer-based analysis of structured and unstructured clinical data, automated data harmonisation, clustering of AF burden phenotypes, and the development
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clinical data, automated data harmonisation, clustering of AF burden phenotypes, and the development of multimodal prediction models to identify clinically relevant disease patterns, predict disease
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task is to monitor automated quality control of the data products and perform additional tests in the days after the measurement. You report on quality issues and make suggestions for improvement. With a
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(Automated Design of Algorithms) group in the machine learning clusters at LIACS, Leiden University, and supervised by Jan van Rijn and Holger Hoos. You will be working intensely with other project members