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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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field Knowledge of freshwater ecology and/or physical limnology Experience with numerical modelling Experience with programming languages, esp. Python, and familiarity in NumPy, SciPy and Pandas
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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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@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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., 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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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
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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