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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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analysing large health datasets, electronic health records, UK Biobank, All-of-Us, or similar sources. Experience with programming in R, Python, C++, Stata, SAS, or other programming languages. Excellent
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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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qualifications: Strong experience in programming using Python, R, or other languages Research experience in remote sensing of cover crop, crop type classification, and crop biomass Insight into global
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with an interest in ecological applications. Required qualifications: PhD (or equivalent) in computer science, biology, software engineering, or a related field Strong proficiency in Python, including
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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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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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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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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
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: Experience with numerical climate models and/or chemical transport models such as CESM and/or GEOS-Chem. Advanced programming skills in Python, Fortran, or other relevant languages. Experience in wildfire