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techniques such a random forest and artificial neural networks for data classification and regression (including uncertainty estimation). Working with project partners to co-design tools to quantitatively
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and Forest Research). The successful applicant will work directly with the ACCESS leadership team to champion the development of environmental social science, including contributing to new research in
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information please contact Prof Zena Wood, e-mail [email protected]
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