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models to enhance the detection of online narratives. The successful candidate will be appointed to a two-year fixed-term, research-intensive position supported by ASCA’s EDT program on synthetic media and
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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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making and machine learning, with real-world testing and feedback. The successful applicant will work on decision making for anomaly detection, behaviour analysis and surveillance decisions, under
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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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, contact: Adriano Catalano Executive Assistant P: +61 (8) 313 9000 E: adriano.catalano@adelaide.edu.au You'll find a full position description and/or selection criteria below: (If no links appear, try
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@adelaide.edu.au You'll find a full position description and/or selection criteria below: (If no links appear, try viewing on another device) We are an Equal Employment Opportunity employer committed to providing a
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Institute - SAiGENCI, and Adelaide Centre for Epigenetics – ACE. E: luke.isbel@adelaide.edu.au You'll find a full position description and/or selection criteria below: (If no links appear, try viewing
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the Cancer Epigenetics Program at the South Australian immunoGENomics Cancer Institute – SAiGENCI. E: qi.zhang@adelaide.edu.au You'll find a full position description and/or selection criteria below
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identified. For further information For a confidential discussion regarding this position, contact: Dr Fatwa Adikusuma (Research Group Leader) Fatwa.adikusuma@adelaide.edu.au You'll find a full position
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Kishan Dholakia ARC Laureate, School of Biological Sciences P: +61 (8) 8313 6761 E: kishan.dholakia@adelaide.edu.au You'll find a full position description and selection criteria below: (If no links appear