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speed - Provide human experts with a reliable second opinion This project integrates image processing, data analytics, machine learning, and computational modelling, with applications in aerospace
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-scale metagenomic assembly and genome recovery • Comparative genomics and molecular evolution • Machine-learning-based protein prediction • Data integration, bioinformatics and phylogenetics • Scientific
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in the fields of machine learning, epidemiology, big data analysis, and suicide and self-harm. Your work will expand the frontier of machine learning applications in epidemiology and improve our
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collaborations, macaque electrophysiology. We use machine learning techniques for data analysis and computational modelling with a special interest in biologically-inspired deep learning and AI models (NeuroAI
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self-harm rates. You will expand your data wrangling, analytical and programming skills on python and develop expertise in the fields of machine learning, epidemiology, big data analysis, and suicide and
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interaction, signal processing, data science and machine learning. The successful candidate will gain expertise at the intersection of structural health monitoring, railway engineering, and advanced artificial
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their pandemic potential and classification as bioweapons. This project aims to develop a machine learning-accelerated NMR platform for the discovery of high-affinity inhibitors targeting viral RNAPs. Building
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using cutting-edge computational techniques, including machine learning algorithms. Work collaboratively with an interdisciplinary and international team to refine and validate regional wave and ocean
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intensity of these changes. This PhD project will ultimately enable aircraft to reroute safely and efficiently in real time as weather evolves. By merging scientific machine learning, large-scale data
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training dataset of well-studied volcanoes with known large eruptions, the project will employ statistical and machine learning (ML) methods to identify the strongest predictors of eruption magnitude