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an outstanding and dynamic environment for PhD candidates, with multiple seminars, working groups, colloquia, and a doctoral school, which also gives access to multiple training opportunities, including courses
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analyses by age, ethnicity, and index of multiple deprivation will be performed. The second stage of the study will involve the analysis of prospectively collected EQ-5D-5L data from a cohort of patients to
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This PhD project focuses on strengthening network security for large-scale distributed AI training. As training increasingly spans multiple data centers connected over wide-area networks, it
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in the Power Electronics Group at UT and collaborate with experts from Seine Batteriesysteme, NRG2Fly, and multiple airports. The project also supports open-source developments in MW-charging protocols
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personalized mentorship from experienced professionals to accelerate your growth Collaboration. Work in an open environment that allows you to collaborate with multiple teams and get exposure to different groups
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personalized mentorship from experienced professionals to accelerate your growth Collaboration. Work in an open environment that allows you to collaborate with multiple teams and get exposure to different groups
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from multiple high-income countries, including the UK (UKHLS), Germany (SOEP), Australia (HILDA), and the US (PSID), alongside ageing studies such as SHARE, ELSA, and TILDA. Where feasible
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students and senior researchers from multiple disciplines to tackle challenges in sustainable aluminium through AI-driven microstructural analysis. The NEST-WISE project offers a vibrant collaborative
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—remains a critical challenge. This project will focus on designing AI-driven cognitive navigation solutions that can adaptively fuse multiple sensor sources under uncertainty, enabling safe and efficient
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experimental partners within the RTG2861-PCL consortium. Specific requirements: We are looking for a motivated candidate, preferentially with theoretical background and strong interest in electronic-structure