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Experience with volumetric image data Excellent programming skills (e.g., Python, C++, MATLAB) and familiarity with scientific libraries (ITK/SimpleITK, VTK, TensorFlow/PyTorch, etc.) Ability to work
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the following areas. You have a background in tissue-based molecular research and experience with tissue sectioning and the generation and analysis of spatial molecular data. Programming expertise in Python and R
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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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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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., 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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evaluations Solid programming skills in at least one relevant language (e.g., Python, C++) Interest in interdisciplinary work involving engineering, sustainability, and real-world infrastructure Strong written