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, or mathematically founded data science as well as excellent oral and written English language skills. Experience with spatial statistics is an advantage. The applicant must hold an MSc degree in mathematical
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or Computer Science; Human-computer Interaction, Spatial Cognition or related areas; Engineering, Applied Mathematics, Statistics or another Quantitatively Oriented Discipline. Application procedure Your complete
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Computational Sciences or similar. You have strong expertise on analyses of biology-related large datasets. Expertise in single-cell and spatial data analysis, spatial statistics and annotation is an advantage
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a PhD in biology, earth system or data science, or a similar field, and have several years of experience with interdisciplinary collaborations focused on understanding biodiversity dynamics by
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with the help of external research funding. Teaching and supervising students at the Bachelor's and Master's level and supervision of PhD students Involvement in assessment and committee work at Aarhus
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documented strong qualifications in mathematics, statistics, or mathematically founded data science, as well as excellent oral and written English language skills. Experience with spatial statistics is an
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spatial analysis. You will design and implement large-scale surveys, manage data collection and cleaning, and carry out rigorous statistical analysis of survey data. You will apply and further develop
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. The duration of the position is three years. Your work tasks In this PhD position, you will work with the spatial and temporal dynamics of shallow groundwater in urban areas. The overall aim is to obtain a
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infrared spectroscopy, simultaneous Raman spectroscopy, and co-located fluorescence imaging. This combination enables label-free chemical identification and high-resolution spatial mapping of plastics and
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for efficiency monitoring and fault detection, combining sensor data, system layout knowledge, and physical principles to extract spatial-temporal features and predict equipment behaviour; 2) Statistical anomaly