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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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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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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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, 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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entry and data validation techniques. Able to query and maintain computer databases. Must demonstrate a critical and intelligent attention to detail including high standards of accuracy. Ability to work
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with information of a confidential nature. Aptitude for learning and applying new skills, and once trained have the ability to work independently to gather information or simply finding missing
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based on sound evidence. Our Birmingham Professional programme operates across the University, supporting colleagues to network and collaborate, offering opportunities to learn and develop, contributing
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of Birmingham Background The School of Chemical Engineering is organised into three primary research themes: formulation engineering, energy, and healthcare technologies. The school's practical learning and