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therapy. Recent advances in digital pathology and innovative data analytics including machine learning have enhanced our ability to identify clinically relevant spatial characteristics of TMEs [1]. In lung
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. Experience of scientific writing. E4. Experience in analysing NGS data. E5. Experience in statistical programming (e.g. R or related software, or machine learning applications). E6. Proven ability to deliver
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the development of valuable transferable and personal development skills, such as finance-oriented computer programming, presentation and professional writing skills. As a PhD student in Accounting
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supervision and development/mentorship/coaching of early career academic colleagues in subject area/team. Experience Essential: E1. A track record of integrating machine learning and/or computational biology
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human mobility within Cities and machine learning approaches School of Social and Political Sciences (SPS) PhD Scholarships Support Support The College of Social Sciences Graduate School draws together
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protein expression across tissues and developmental stages, quantifying correlations between transcript and protein levels. Using machine learning, we will identify conserved expression profiles
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protein expression across tissues and developmental stages, quantifying correlations between transcript and protein levels. Using machine learning, we will identify conserved expression profiles
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variety of CAI’s across all chondritic meteorites, machine learning analytics will be employed on a range of microscopy data sets, both archival and freshly acquired. Starting from optical micrographs a
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to recognise the shape, size, and materials of urban features, through the application of statistical, machine learning (ML) and artificial intelligence (AI) techniques. The use of freely accessible raw GNSS
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conferences. PhD: 3 years full-time; 5 years part-time; Thesis of 70,000-100,000 words MLitt (Research): 2 years full-time; 3 years part-time; Thesis of 40,000-70,000 words MPhil (Research): 1 year full-time; 2