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PhD Studentship: Preclinical modelling and therapeutic targeting of glioblastoma infiltrative margin
revealed distinct gene expression profiles of the infiltrative margin of glioblastoma via bulk transcriptomics https://pubmed.ncbi.nlm.nih.gov/37434262/ predicated on biopsies obtained via 5-aminolevulinic
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the University College London (UCL) invites applications for a fully funded 4-year PhD program in Process Systems Engineering. The project will focus on the development of an AI-enhanced design framework for novel
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on the lab can be found at https://www.sysneurodevlab.org/ Eligibility & How to apply: Please submit a formal application using the online admissions portal (via the ‘Apply’ button above) attaching a CV
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, or Have pre-settled status (meeting residency requirements), or Have indefinite leave to remain or enter Further guidance can be found here - https://www.ukri.org/wp-content/uploads/2021/02/UKRI-030221
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Fully-funded PhD Studentship in Metamodelling of Speech Domains School of Computer Science PhD Research Project Directly Funded Students Worldwide Prof Thomas Hain Application Deadline: 19 April
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Department: Faculty of Science AI Doctoral Training Centre Programme length: 42 months Closing date: 19 April 2026 The Faculty of Science AI Doctoral Training Centre (DTC) invites applications from
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integration. About This PhD This PhD programme is part of a prestigious £8M EPSRC Programme Grant on Advanced Integrated Motor Drives (AIMD), a major research initiative launched in 2025. You will work on the
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at Nottingham https://www.nottingham.ac.uk/coatings/ is an international reference for all Thermal Barrier Coating activities. This PhD programme, in partnership with Rolls-Royce, will address key challenges
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and to study on this programme. How To Apply You must apply through the University’s Application Portal: https://applyto.newcastle.ac.uk/ In ‘Course choice’ tab: Type of Study - ‘Postgraduate Research
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) invites applications for a fully funded 4-year PhD program in Process Systems Engineering. The project aims at integrating data-driven optimisation and design of experiments techniques with model-based