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various data analysis tasks. Your work will focus on carrying out data preprocessing, data wrangling, and carrying out analyses using R (and sometimes Python). Example projects you will be working
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@au.dk) Applicants must have a relevant PhD degree in biology, biogeochemistry, hydrology, glaciology, oceanography, geoscience or physics. Field experience, data analysis and programming (e.g., python
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programming skills in R and Python. Experience with content coding of verbal descriptions Good communication and teamwork skills. Interest in autobiographical memory and moral psychology. Some experience with
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and Memorial Sloan-Kettering Cancer Center, NY. Read more about the project here: https://health.medarbejdere.au.dk/en/display/artikel/supercomputer-and-ai-to-strengthen-danish-cancer-treatment-new
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., CNNs, UNets, Transformers) Demonstrated experience working with satellite data, particularly SAR and multi-spectral imagery Strong programming skills in Python and hands-on experience with deep learning
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university, seeks top students for attractive PhD stipends. The call is open until 1 February, 2026, with the earliest start date, 1 May, 2026. Please find more details and apply at https://math.au.dk/en/about
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programming skills (advanced Python preferred). Willingness and ability to participate in international fieldwork multiple times per year, including field campaigns in Ethiopia lasting up to 2–3 weeks
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with AI/ML implementation, particularly for sensor data processing, feature learning, or autonomous system control Solid software development skills in languages such as Python, C/C++, or similar, with
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Programming skills in Python, R, and/or GIS tools Highly valued: Background in LiDAR point-cloud analysis and vegetation structure analysis or habitat monitoring Experience applying AI or machine learning
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handling and processing, including import, cleaning, filtering, and visualization of data in R, Python, or similar tools. Experience with planning and execution of measurement campaigns. Fluency in spoken