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or integrated pest management with hands-on experience in agricultural field trials solid knowledge of statistical analysis and publication of research results first experience in acquiring third-party funding is
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or a related discipline A solid background in climate and atmospheric sciences, and extreme weather ideally supported by knowledge of machine learning and time series analysis is of advantage, as is
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phenotyping, including image analysis evaluations, for trait quantification Handle NGS datasets for RNAseq or SNP detection and linkage analysis using R Your qualifications and skills: You have a PhD or
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The Network Analysis and Modelling group investigates how genetic variation shapes gene regulation, protein function, and, ultimately, observable plant traits. Using machine learning and network
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, aggregation, linking and retrieval of comprehensive heterogeneous and distributed data sources. To this end, both statistical and linguistic analysis methods (NLP) as well as machine learning in combination
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developing computer-vision systems for faunistic data analysis Present project goals and achievements in national and international scientific conferences Supervise technicians and students in training data
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on two core but complementary areas: Computer vision and sensor data analysis, applied to tasks such as object detection in drone images (e.g., pest or disease detection), object tracking (e.g. leaves
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). The empirical research should capture and analyze teaching and learning processes, for example by video analysis or eye-tracking. Development activities for instance may include AI tools, the creation
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analytical skills which bridge science and marine policy, including research experience in European coastal and marine systems. Experience in spatial data analysis using geographic information systems (GIS
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in spatial equilibrium modeling (e.g., through coursework, dissertation work, or previous projects) experience with spatial data analysis using GIS tools or spatial libraries and familiarity with