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& Managing CO₂ Artificial Intelligence & Robotics This is ambitious work - work that demands curiosity, courage, and a relentless drive to make a difference. At EIT, you’ll join a community built on excellence
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& Managing CO₂ Artificial Intelligence & Robotics This is ambitious work - work that demands curiosity, courage, and a relentless drive to make a difference. At EIT, you’ll join a community built on excellence
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wishes to recruit a Postdoctoral Research Associate to further the work of the Westra and van Houte research teams on the development of synthetic phage therapy. The successful applicant will be
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, mathematical finance, or optimization and is capable of actively contributing to research projects in these fields. The contract start date is flexible, beginning as early as March 1, 2026. The employment
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optimization. AI/ML methods development: Neural networks, graph neural networks (GNNs), generative AI, or active learning for materials applications. Integration of theory and experiment: Using computation and
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: PATHWAYS (www.pathways-project.com ). This 6-month post offers a unique opportunity to work within an experienced and impactful team, collaborating with those promoting innovations in livestock supply chains
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to delivering optimal gout care, by conducting focus groups, stakeholder engagement work, and qualitative data analysis. They will support the development of interventions to address identified barriers
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out research relevant to the Diamond-II synchrotron light source project. The successful candidate will work with members of the Diamond Accelerator Physics Group, investigating topics such as the
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The Department of Physics at Lancaster University invites applications for a Post-Doctoral Research Associate to work in the field of ultrafast magnetism and THz-driven spin switching. The post is funded by EPSRC
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an excellent publication record. Solid research experience in one or more of the following topics is expected: Graph neural networks Optimization algorithms Predicting structured output Self-supervised learning