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-informed machine learning (PIML) with domain-specific engineering knowledge. By embedding physical laws and corrosion mechanisms into data-driven models, the research will produce more accurate
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systems in toxicology and pharmacology. Crit Rev Toxicol. 2021 Jul;51(6):540-554. Jia et al. Advancing Computational Toxicology by Interpretable Machine Learning. Environ Sci Technol. 2023 Nov 21;57(46
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personalised, ethnically-stratified risk scores. This is a highly interdisciplinary project at the intersection of machine learning, health equity, and precision medicine. The successful candidate will join a
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biodiversity. eLife. Eastwood et al (2022) The Time Machine framework: monitoring and prediction of biodiversity loss’. Trends in Ecology and Evolution (Invited opinion paper). Rossi et al (2020). Temporal graph
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are open to adjacent areas that can interface with SERENE’s mission): AI/ML & Data-Centric Space Environment Modelling Machine learning, deep learning, Bayesian methods, or hybrid physics-ML models
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, flight dynamics and operations. Stability and control of air vehicles using novel methods and/or for innovative platforms. Application of novel machine learning approaches to practical future flight
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research and education institution, enabling groundbreaking discoveries and providing an exceptional learning environment for our students. The School boasts a rich history of world-class research and takes
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underpin our research and provide an exceptional learning environment. EESE delivers internationally recognised research and education across communications and sensing, electrical power systems, cyber
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to writing bids Operating within the area of gravitational-waves and astrophysics Applying probabilistic inference to gravitational waves, including through machine learning techniques Modelling
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geotechnical engineering, archaeology, geophysics, sensing and machine learning, with group members from seven different countries, speaking over ten different languages. Perks of this role include: Opportunity