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Fixed-term: The funds for this post are available for 3.5 years in the first instance. Dive into the future of visual technology with a studentship at the forefront of modern imaging science, where
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) advances in imaging techniques that fuel a more detailed understanding of the brain, 2) tools from artificial intelligence that enable building better computer simulations of the brain. The lab will leverage
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wet- and dry-lab scientists that are studying RNA, chromatin and transposon biology, covering all aspects of this RNA-based immune system, including the biogenesis of small non-coding RNAs and the
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. Many novel concrete technologies and mixes are not currently covered by building codes, and it takes considerable time to include new technologies in codes and standards. Lack of routes to validation
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, please state the course code EGEGR3 with Project: Data-Intensive AI Thermodynamic Models for Next-Generation Building Decarbonisation with Prof Dongfang Liang. Please note that there is a £20 application
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processes associated with CIN [1], leveraging single-cell DNA sequencing understand CIN heterogeneity [2], and development and implementation of machine learning and AI models to imaging data [3]. The student
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: Advanced molecular and protein analysis Mass spectrometry-based imaging Multi-omics technologies Preclinical cardiometabolic animal models They will also gain professional development in data stewardship
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https://www.cambridgetrust.org/scholarships/ Applications should be made online via the University of Cambridge Applicant Portal: (via the above ‘Apply’ button) stating course code EGEGR3 with Project
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(current rate) per annum with a top up of £5,500 per annum from Tata Steel. Fees: This position is open to UK citizens or overseas students who meet the UK residency requirements (home fees) or are able
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: This position is open to UK citizens or overseas students who meet the UK residency requirements (home fees) or are able to augment the funds to cover the extra costs associated with international