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No of positions: 1 This 3.5 year PhD project is fully funded at UK rates; the successful candidate will receive a tax free stipend set at the UKRI rate (£20,780 for 2025/26) and tuition fees will be paid. We expect the stipend to increase each year. UK students and those with settled status are...
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PhD Scholarship for The Impact of Future Human Values and Practices on Australia’s Net Zero and Digital Transitions Job No.: 679372 Location: Caulfield campus Employment Type: Full-time Duration
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backgrounds to contribute to our projects in areas such as: Network Security, Information Assurance, Model-driven Security, Cloud Computing, Cryptography, Satellite Systems, Vehicular Networks, and ICT Services
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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