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Field
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connections to their communities and you may be eligible for an exception to this work arrangement. Alternative work arrangements may also be considered to accommodate candidates as required. To learn more
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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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the research themes of software engineering, engineering computing, sensor networks and measurement technology, grid computing and physics data analysis, machine learning, and interactive and collaborative
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biosignals. Application of machine learning techniques for classification of different classes using the extracted features. Assembly, documentation, testing, and use of an innovative biosensing system
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: offshore wind turbines, wave tank experiments, fluid-structure interactions, sensors for offshore structural health monitoring, software development, machine learning and advanced AI modelling, and previous
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a new computational paradigm that combines the versatility of the digital computer with the efficiency of close-to-physics computing. The group targets the full computational stack, from materials
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quantitative genetics, Bayesian methods, machine learning, large-scale genomic datasets, single-cell omics or integrative omics analyses would be highly regarded if the candidate was not initially trained in
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scalable way. This project aims to solve this by combining different kinds of data - structural, functional, and causal - into a single AI-centred computer model. We focus on the larval zebrafish, a small
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experiences on computer vision • Strong programming skills in using Deep Learning tools like PyTorch and GPU clusters. • Good written and verbal communications. • Open to Fixed Term Contract
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focused on using spatial profiling and machine learning of human specimens in combination with functional experiments in animal models to understand cancer initiation, progression, and metastasis. We