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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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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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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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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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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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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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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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such that the tasks outlined in the job description can be conducted effectively. Ability to undertake training to acquire knowledge of the Immigration Rules and Home Office Guidance, particularly in relation