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Intelligence (AI), Machine Learning (ML), and data-driven decision support systems for precision agriculture. The Assistant Professor – AI & Data-Driven Precision Agriculture position is part of a strategic
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, epidemiology, public health, and systems medicine within the framework of precision medicine. We expect the successful applicant to have experience of programming, data analysis, and data mining to identify
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with transcriptomic and/or epigenomic data analysis Strong communication skills and ability to work in interdisciplinary teams Fluency in English, both written and spoken We expect interested and
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, especially in the buildings sector You already have some experience in data analysis and programming with Python or a comparable programming language You are highly motivated and able to work independently and
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Assistant assists with experiments by assisting senior-level researchers in data collection and analysis, as well as multiple lab management tasks. They are expected to work somewhat independently, given
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) to address the relevant research questions. Perform statistical analysis on survey/experimental data, and conduct thematic analysis on interview transcripts and open-ended survey responses. To lead and report
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the other activities within the GOSS group and more broadly within QDLight, notably to benefit from the theoretical expertise required for the data analysis. This work takes place within the GOSS group
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molecular cloning, bacterial cell culture, SDS-PAGE, and Western blotting. - Experience with data collection and analysis using techniques such as chromatography, electrophoresis, and/or spectroscopy
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activity should focus on conducting research on machine learning methods, image processing, and advanced data analysis. Furthermore, participation in research projects, active grant applications, and
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exclusively on the spatial analysis of images, making them sensitive to optical aberrations, difficult to implement in depth, and inherently limited in the type of information they can extract. Our group