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day-to-day, supervised by the project lead and other senior team members, and with some help from another research assistant. This involves liaising with patients to arrange their (online) clinical
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requirements Open to any UK or international candidates. Starting in January 2026. You will need to meet the minimum entry requirements for our PhD programme . By the start of the PhD programme, applicants must
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the successful candidate embarking on a PhD programme at LSHTM. It is anticipated that the role will lead to a further 18 month funded opportunity at Max Planck Institute for Demographic Research (MPIDR), in
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an implementation support package Project Supervisors: Dr Sam McLean Prof Beth Fylan Dr Justine Tomlinson Jaspreet Sohal Project Description: This is a fully funded training programme to conduct research
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machine learning. The position will involve working with different research groups in the Department of Computer Science at the University of Cambridge, UK. In this collaborative project, we will apply
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collaborative studentship between the University of Edinburgh and the National Quantum Computing Centre (https://www.nqcc.ac.uk ). The position will be registered and hosted at the University of Edinburgh and
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senior researchers and experts in the field. They will be fully embedded into the highly collaborative and interdisciplinary research environment of the Costantini Lab . Their work will be firmly rooted in
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consumables, equipment, and travel related to the project. Number Of Awards ReNU+ is a unique and ambitious programme that will train the next-generation of doctoral carbon champions who are renowned
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for Security Operations Centres (SOCs) while pioneering strategies for quantum-era resilience. This project sits at the intersection of Artificial Intelligence, Cybersecurity, and Explainable Computing. It
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of senior researchers and will perform research necessary to fulfil the objectives of the Project Identification of therapeutic targets in MNX1-rearranged infant Acute Myeloid Leukaemia, externally sponsored