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for policy, practice and advocacy. The mixed-methods project will use a combination of participatory approaches including but not limited to GIS mapping, stakeholder analysis, network and systems mapping
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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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Matlab, Python or similar. The position is located at Curtin University in Perth, WA Application process Please contact us via the EOI form with the following Curriculum vitae Academic transcripts A brief
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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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microfluidic fabrication and experiments 3D printing machine learning. Demonstrated programming skills (Matlab, C++, or Python). Desired Demonstrated ability to work independently and to formulate and tackle
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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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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
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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