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, for the preparation of a doctorate, contains: We invite you to apply for a PhD position supported by the Marie Skłodowska-Curie Doctoral Network HARNESS - Harnessing AI and Data-Intensive Technologies
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This studentship is offered by the EPSRC Centre for Doctoral Training in Robotics and Artificial Intelligence for Net Zero Centre (RAINZ) which is a partnership between three of the UKs leading
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This studentship is offered by the EPSRC Centre for Doctoral Training in Robotics and Artificial Intelligence for Net Zero Centre (RAINZ) which is a partnership between three of the UKs leading
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an active student scene and a diverse cultural life. We are looking to fill a PhD position (m/f/d) - Top-down partitioning of net ecosystem exchange (NEE) on regional scales for 3 years, starting in September
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PhD Scholarship – Modelling the social and political drivers of net zero transitions Job No.: 670767 Location: Clayton campus Employment Type: Full-time Duration: 3.5-year fixed-term appointment
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Reference: RD-PHD-01-DM-MH-25 Project Title: Optimum strategies for UK beef producers to achieve net zero Primary supervisor: Daniel May Co supervisors: Karl Behrendt and Jude Capper Expected Start date and
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model of reaction barriers. This will enable the development of more accurate and advanced high-throughput reaction network discovery and by-product prediction. Background Typical drug molecules can
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11.11.2024, Wissenschaftliches Personal In the project “BIG-ROHU” (BIG Data - Rotor Health and Usage Monitoring), a system is being developed which provides information on both the health and the actual stress of helicopter components using a data-based as well as a physics-based approach. In...
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, the internal workings of deep neural networks remain largely mysterious, posing a significant challenge to the interpretability, reliability, and further advancement of these models. This project seeks deep
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, artificial neural networks and bio-inspired robotics: "Rhythmic-reactive regulation for robotic locomotion" (Supervisor: Prof Fulvio Forni) will apply techniques from nonlinear control and optimisation