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combinations of theoretical physics, mathematics, and machine learning. While machine experience is not a strict requirement for the job, we anticipate that the strongest candidates will have clear research
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We are seeking a highly talented and experienced Postdoctoral Researcher to join a research team led by Prof Chris Summerfield focussed on studying learning and decision-making in humans and machine
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years of post-qualification experience at the time of application; (b) experience in using machine learning for research projects; and (c) have a good command of both written and spoken English
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The Atmospheric Chemistry Research Group (ACRG) and School of Engineering Mathematics at the University of Bristol have developed GATES, a graph neural network (GNN) machine learning model that can
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machine learning approaches to quantitatively analyze experimental data and predict emergent multicellular behaviors under varying mechanical and chemical environments. For more information about our lab
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, statistical software, biostatistical software) Understanding of bioacoustic principles Desirable knowledge: programming skills (preferably python or R), knowledge of machine- and deep learning, bioacoustic
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Disse), the Chair of Geoinformatics (Prof. Thomas H. Kolbe), and the Chair of Algorithmic Machine Learning & Explainable AI (Prof. Stefan Bauer). The project aims to develop an integrated urban flood
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, 2026, in one of the following projects: • Stress response markers and behavioural changes in viral C'S infections (Project P01: Prof. Dr. Sonja Bröer) • Analysis of a non-invasive method to determine
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can email the supervisors directly at: Prof Zhongdong Wang (zhongdong.wang@mancheser.ac.uk ) and Prof Peter Crossley (peter.crossley@manchester.ac.uk ).
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The role The Atmospheric Chemistry Research Group (ACRG) and School of Engineering Mathematics at the University of Bristol have developed GATES, a graph neural network (GNN) machine learning model