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Regular/Temporary Regular Job Code 9521 Employee Class Grad/Prof Student Position Add to My Favorite Jobs Email this Job About the Job Graduate Assistantship, RIDGS Ethnic Studies Initiative (50% Academic
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, resulting in faster and more cost-efficient signal modelling. However, embedding physical constraints within the network architecture remains a significant challenge. Current research often integrates
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or compromised IoT devices by analysing encrypted traffic patterns, focusing on metadata, flow characteristics, and timing rather than decrypting payloads. The core challenge is creating features and models
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research addressing one or more of the current ecological crises (e.g., climate, pollution, biodiversity) from a broadly social cognition angle. Desirable research frameworks to explore these topics include
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or more of the current ecological crises (e.g., climate, pollution, biodiversity) from a broadly social cognition angle. Desirable research frameworks to explore these topics include cognition and emotion
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2025 Reference: RD-PHD-01-LS-MH-25 Project Title: The cost of silage production: measuring the carbon footprint of silage Primary supervisor: Prof. Liam Sinclair Co supervisors: Dr Kate Le Cocq, Dr
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model complexes. This research is part of a large, funded collaborative project supported by the Swiss National Science Foundation, involving partner researchers based in Germany, Switzerland, and France
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Measurement Frameworks. Project Overview: The Science & Technology Entrepreneurship Education and Research (STEER) project will create best-practice teaching models, scholarly research, and scalable
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modelling capabilities for the prediction of energy extraction efficiency, especially focusing on improving the understanding and prediction of the complex flow phenomena, including buoyancy effects in AGS
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contact the supervisors; Dr Mingfei Sun - mingfei.sun@manchester.ac.uk and Prof Samuel Kaski - samuel.kaski@manchester.ac.uk . Please include details of your current level of study, academic background and