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, AquaCrop) or experience with agricultural or environmental modelling. Some experience with programming in R and/or Python. Exposure to climate or weather data, forecasting systems, or geospatial tools
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algorithms and deep learning models. Have proficiency in Python in a Linux environment and development experience using Tensorflow or PyTorch. Have strong linear algebra and computer vision knowledge. Have
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science and machine learning Knowledge with Python or Matlab. Application process Please send your CV, academic transcripts and brief rationale why you want to join this research project via the HDR
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, problem-solving and project management skills. Candidates with strong quantitative skills, including familiarity with python and astronomy are desired for this project. Must be eligible to enrol in PhD
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developing scientific software (using any of these languages/libraries: Python, Julia, C++, C, Fortran, Matlab, Fenics/FeniX, MFem, deal.II, libMesh, PETSc, Trilinos, Pytorch, TensorFlow, Jax, Keras, Pandas
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essential. Excellent organisation and problem solving skills are expected and experience in data wrangling, processing and visualisation using R or Python would be advantageous but not essential
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with Python or C. Solid understanding of linear algebra, calculus, and probability theory. Strong background in machine learning and deep learning is highly preferred. The ideal candidate will have