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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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proficiency in R or Python and version control systems like Git. Familiarity with spatial and statistical libraries (e.g. INLA, PyMC, scikit-learn, GeoPandas). Proven ability to work independently. Track record
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programming experience with Python and/or Matlab Experience with advanced MEG/EEG signal processing and/or machine learning is desirable Strong interest in translational research and developmental neuroscience
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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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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 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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: 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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of neural network architectures (as a plus: PINNs, neural operators, transformers/LLM) and NN training. Strong Python programming skills (as a plus: C++ or Julia) and knowledge of scientific computing