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proposed PhD project is our standard entry, however we place value on prior experience, enthusiasm for research, and the ability to think and work independently. Excellent Analytical skills and strong verbal
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relevant to the proposed PhD project is our standard entry, however we place value on prior experience, enthusiasm for research, and the ability to think and work independently. Excellent Analytical skills
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Overview We are inviting applications for a Research Assistant to support the following project Next-Generation Forest Inventory (NextGen-FI): Open-Set Recognition for Monitoring Illegal Logging
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4-year PhD fellowship in the Research Programme - Deep Learning-Accelerated Crystallography Pipeline
. Job description Your key tasks are: Carrying out an independent research project under supervision, including deriving its mathematical basis and implementing results in code; Completing PhD courses
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Primary supervisor - Dr Thomas Anthony Haynes Pellet-clad interaction (PCI) is a complicated phenomenon, relatively poorly captured in current commercial fuel performance codes. Models have been
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developed mouse models and human tissue processing pipelines. The candidate will learn and use cutting edge immunological methods (high parameter flow cytometry, multiplex imaging, single cell and spatial
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of breast cancer patients (the largest of their kind; making extensive use of imaging mass cytometry and spatial transcriptomics) that span observational studies and clinical trials. We must precisely define
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models ranging from baseline approaches to graph neural networks. You will also oversee the open release of project datasets, models, code and documentation. The successful candidate will join Oxford's
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must be made through the university’s on-line application system https://admissions.bham.ac.uk/course-finder-landing-page/?code=EPS006 . Please provide: (1) a cover letter summarising your research
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through the University’s Apply to Newcastle Portal In ‘Course choice’ tab, put ‘Postgraduate Research’ in 'Type of Study', ‘Full Time’ in ‘Mode of Study’, ‘2026’ in ‘Year of Entry’, code ‘8420F’ in ‘Course