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Field
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the assembly, management, and analysis of complex datasets, including the application of machine learning techniques to develop a range of models such as predictive and image-recognition models. A key aspect of
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for tumor behavior and clinical outcomes Development and implementation of artificial intelligence and machine learning algorithms for biologically and clinically motivated questions in pediatric oncology
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implement data management and analytics protocols for clinical trial datasets Apply deep learning and AI to time series neuromonitoring data Build and test predictive models using machine learning techniques
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data-driven engineering methods, particularly those leveraging artificial intelligence or machine learning. Key Responsibilities & Accountabilities 1. Initiate, Execute, and Complete Advanced
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competence in statistical modelling, machine learning, artificial intelligence, causal inference, prediction modelling or related quantitative methods. Experience with analysis of large, complex health data
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: The appointee will be involved in the full lifecycle of research projects, from study design to publication. This includes development of machine learning models, computer simulations, and app/software
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denoising, cell segmentation and the analysis of cellular neighbourhoods and cell–cell interactions. Experience in developing artificial intelligence and machine-learning methodologies for multimodal data
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chip packaging F5 Experience using data analysis or machine learning tools for electronics reliability or sustainability assessment F6 Experience with rapid prototyping technologies (3D printing, laser
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supporting documentation, proven experience in all of the following areas: Computer vision and video processing (ingestion, ROI, 2D/3D keypoints, heatmaps); Deep learning and temporal modelling (CNNs
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AUSTRALIAN NATIONAL UNIVERSITY (ANU) | Canberra, Australian Capital Territory | Australia | 3 months ago
system and user behaviour. Join a growing portfolio of projects in artificial intelligence, natural language processing, and machine learning. These projects build on the School’s strengths in AI, machine