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into goal-directed behavior. We use state-of-the-art approaches including functional brain imaging, automated behavioral analysis, and computational neuroanatomy. We value a collaborative atmosphere, early
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operation of autonomous systems in complex, real-world conditions. This PhD project aims to develop resilient Position, Navigation and Timing (PNT) systems for autonomous transport, addressing a critical
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, Reliability and Trust (SnT) at the University of Luxembourg is a leading international research and innovation centre in secure, reliable and trustworthy ICT systems and services. We play an instrumental role
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contribute? You will contribute to a project developed within the framework of a long-standing collaboration with Pierre Fabre, who are a global leader in pharmaceuticals and dermo-cosmetics. The work will
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work may suit applicants from a mathematics, computer science, or data science background. A demonstrable understanding of, and passion for, psychological research is essential. Candidates should be able
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compounds in collaboration and support with experienced radiochemists. The candidate will acquire and analyze PET/SPECT imaging data, perform kinetic modeling, and contribute to advanced image analysis
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the objectives of the aforementioned consortia. These projects work at the interface of the gut microbiome, diet, and the immune system to investigate their roles in various diseases, including but not limited
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in a subject relevant to the proposed PhD project (such as mathematics or theoretical physics) is our standard entry, however we place value on prior experience, enthusiasm for research, and the
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Deadline: 30 June 2025 A fully funded four-year PhD position is available to work on the project titled “Real-world quantum verification and benchmarking of noisy hardware”. This position is a
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AI-Driven Digital Twin for Predictive Maintenance in Aerospace - In Partnership with Rolls-Royce PhD
datasets with industry-aligned performance metrics. The successful candidate will join the Centre for Digital and Design Engineering (CDDE), part of Cranfield’s Manufacturing, Materials and Design theme