20 bayesian-object-detection Fellowship positions at University of Adelaide in Australia
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metapopulation and/or individual based models Knowledge of Bayesian methods, including Approximate Bayesian Computation Experience with big data analysis and HPC environments Knowledge of additional programming
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months only to find they are worthless at harvest. This project aims to develop new capability to detect and measure volatile agents directly in smoke, allowing growers to make more cost-effective vineyard
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. The objective of this project is to explore how Physics-Informed Neural Networks (PINNs) could enhance the detection, classification, and interpretation of weak and noisy signals in complex environments
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For a confidential discussion regarding this position; contact: Alessia Rotolo Senior Talent Acquisition Officer | Human Resources E: alessia.rotolo@adelaide.edu.au You'll find a full selection criteria
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Professor, Weed Management School of Agriculture, Food & Wine Ph: +61 8 8313 7237 e-mail: christopher.preston@adelaide.edu.au You'll find a full selection criteria below: (If no links appear, try viewing
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@adelaide.edu.au You'll find a full selection criteria below: (If no links appear, try viewing on another device) The University reserves the right to close this advertisement before the closing date if a suitable
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: giuseppe.tettamanzi@adelaide.edu.au You'll find a selection criteria below: (If no links appear, try viewing on another device) The University reserves the right to close this advertisement before the closing date if a
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: Professor Abelardo Pardo Head of school of computer and Mathematical Sciences Faculty of Sciences, Engineering and Technology P: +61 8 8313 3217 E: abelardo.pardo@adelaide.edu.au You'll find a full position
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30828 E: tafsirojjaman@adelaide.edu.au You'll find a full position description and/or selection criteria below: (If no links appear, try viewing on another device) The University is an Equal Employment
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members including academics, research staff, and students. The institute works on a mixture of fundamental and commercially oriented research projects in computer vision and machine learning. Find out more