100 assistant-professor-computer-science-data-"https:"-"https:"-"https:"-"https:"-"UCL" positions at University of Glasgow
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Job Purpose We are seeking a highly motivated Computer Scientist to advance tissue-based research through innovative computational and artificial intelligence (AI) approaches to pathological images
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excellent. 7th in UK: Complete University Guide [Computer Science] UK top 20: Guardian University Guide [Computer Science & Information Systems] UK top 10: Times & Sunday Times Good University Guide
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Overview Our Geospatial Data Science programme is suitable for students wishing to pursue a PhD and undertake innovative research in a wide range of subjects which aligns to one of our Geospatial Data
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our organisation, and we will invest in you too. Please visit our website https://www.gla.ac.uk/explore/jobs/ for more information. Closing date: 23:45 on Wednesday 4th March 2026
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help in the assessment of the effect of restoration on water quality. Potential data types that could be of interest include (but are not limited to) – GFT Water quality data, SEPA flow data, geology
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, Veterinary & Life Sciences through one-to-one sessions, open drop-ins, and themed workshops/classes on specific topics; to aid in the creation of online teaching resources; and to assist in the delivery
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questionnaires; collecting other personal data, assisting with participant recruitment, conducting observations, and study associated administration. Data collection will be completed in a variety of community
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understanding of the nature of information and innovative solutions that connect theory with practice, people with information, and technology with humanity. Our research focuses on the following areas
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well as contribute to understanding the development of rRNA fragmentation in Myzozoan parasites. A successful candidate will have proven skills in computational biology and a working understanding of structural
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imaging, spatial data analysis, and machine learning. One arm of the project will seek to engineer diverse quantitative features (e.g., adapting concepts and metrics from network science [5] to characterise