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The primary objective of this project is to establish the evidence base on professional cycling road ‘racing’ trends and the critical tactical moments that determine how races are won. This evidence
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supporting the Net Zero 2050 target. This PhD project will develop an AI-enabled framework that optimizes wind turbine control and predictive maintenance. Using Deep Reinforcement Learning (DRL), the system
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Description TUD Dresden University of Technology, as a University of Excellence, is one of the leading and most dynamic research institutions in the country. TUD has established the Collaborative
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development and refinement accordingly. We are looking for a highly organised, driven, and dynamic individual who is a team worker, has a positive outlook, and is adaptable and flexible in their working methods
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PhD position in the field of climate dynamics Faculty: Faculty of Science Department: Department of Physics Hours per week: 36 to 40 Application deadline: 31 August 2025 Apply now How does a
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filled The overarching aim of this project is to find synergies between methods and ideas of modern machine learning and of statistical mechanics for the study of stochastic dynamics with application
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real-world applications? Are you fascinated by how the local dynamics of nearest neighbour models can determine the macroscale behaviour of a system? Do you want to understand how matter self-organizes
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Organisation Job description PhD position: ML based implementation of constitutive behavior of stainless steel Metal forming is a widely used method to form steel products efficiently in mass
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of methane dynamics in rapidly changing ecosystems and contribute to improving predictive models of future methane emissions. Field sampling will focus on regions where methane cycling is still poorly
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. Applications may close early if the position is filled before this date. Please note that any offer of funding will be conditional on securing a place as a PhD student. Candidates will need to apply separately