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Cranfield University invites applications for a PhD funded by Thames Water through the Ofwat Innovation Fund. The studentship covers full Home tuition fees plus a taxfree stipend of £24,000 per year
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materials systems at the molecular level with machine learning. The PhD Student will undertake a study analysing mass spectral imaging data streams in real time using machine learning workflows. A pathway for
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materials systems at the molecular level with machine learning. The PhD Student will work with tumour sections to develop multiple instance learning and weak supervision / spatial transcriptomics models
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during these assessments, and take appropriate action when needed. - Accurately enter and update subject data into databases as needed. - Assist the Lab Manager and PhD level Research Associates in
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transformations of industrial importance. The PhD candidate will become a member of an enthusiastic interdisciplinary research team, which combines experimental and computational tools in the development of novel
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international work environment Scientific excellence and extensive professional networking opportunities A structured PhD program with a comprehensive range of continuing education and networking opportunities
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Max Planck Institute for Extraterrestrial Physics, Garching | Garching an der Alz, Bayern | Germany | about 4 hours ago
Physics invites applications from talented, ambitious graduating MSc students for a PhD position on Exploring Supernova Remnants in eROSITA and Multiwavelength Data (m/f/d) Job Code: 16/2025 The PhD project
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fully funded PhD research studentship in Physics-Informed Machine Learning for Cardiovascular Medicine. This opportunity is open to UK (Home) candidates only. Project Overview Arrhythmias are disorders
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record of scientific productivity is preferable. The successful applicant must have a Ph.D.in Computer Science, Data Science, Statistics, Mathematics, Physics, Engineering or related field at the start of
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The National Industry PhD Program is an Australian Government initiative to enhance workforce mobility among graduate researchers, and to promote knowledge transfer between academia and industries