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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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@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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(e.g., R, Python). Proven ability to publish at a high international level. It is a prerequisite that you are good at communicating in English. Strong collaborative skills and good collaboration skills
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assessments. Key responsibilities Design and conduct experiments. Operate and maintain gas measurement equipment and flux chambers. Process, analyze, and visualize large data sets using Matlab, R, Python
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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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demonstrate: Experience with optical spectroscopy, and ideally with terahertz technology. Experience with hardware control using Matlab, Python, or similar tools. Experience with machine learning algorithms and
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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
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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