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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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reliability of R-Mode, particularly under varying environmental conditions. Key objectives include understanding the physical processes that affect R-Mode signal propagation, quantifying the variability
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development efforts for ERGOM. The primary objective of this position is to generate high-resolution seagrass distribution maps for the Baltic Sea, achieving a spatial resolution of approximately 1 nautical
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track record in data modelling, machine learning and deep learning Previous research achievements supported by peer-reviewed publications Excellent knowledge of statistical/machine-learning and deep
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relation to the use of syntactic structures in coordination with various bodily resources, such as gaze, facial expression, object use, movement in space, etc. Your tasks will involve collecting and
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equivalent degree in agriculture, biology or any related field. You are an early career researcher not more than one year after your PhD and you have a proven track record and extensive experience with genetic
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ecology, macroecology, metacommunities, and/or analysis of ecological time series. The applicant should have a strong track record of scientific publications. Over the past years, we have compiled one
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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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questions at the interface of community ecology and evolutionary biology. The project's main objective will be to test how interactions between specific processes of community ecology (species sorting