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theory, and machine learning applications in physics. The initial appointment is for one year, renewable for up to two additional years, depending on research performance and funding. Applicants should
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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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Job Description The Virginia Tech Institute for Advanced Computing (IAC), in partnership with the Departments of Computer Science (CS) and Electrical and Computer Engineering (ECE), invites
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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
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of robust, wearable neurotechnologies. This role offers an excellent opportunity for a researcher with expertise in neural signal processing and AI/machine learning for the analysis, classification, and