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(University of Bristol). This project seeks to deliver a step-change in how we understand the dangerous eruptive transitions that are associated with significant disruptions and fatalities. The project will use
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subdivisions of the squamate body plan. The candidate will work towards developing computational resources that assist in the data management and analysis of genomic data and its integration with phenotypic data
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data analysis/spectral image processing. Use of data analytics or machine learning to guide process design and optimization. Job Family Postdoctoral Job Profile Postdoctoral Appointee Worker Type Long
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work with a team of approximately 20 researchers in the built environment group at CUPR and will contribute research skills and training at the intersection of engineering and public policy with
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intelligence, AI-based data analysis, transcriptomics, proteomics, genomics or spatial omics. Interdisciplinary background or interest. A focus on Wet Lab research development. Candidates with experience
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for data science (Python, R, SQL, PostGIS, GeoPandas, etc.). Knowledge of urban models and spatial analysis tools (urban growth models, accessibility, change detection, etc.). Ability to work with
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Research Associate position, with the possibility of extension based on an annual basis dependent upon satisfactory performance and the availability of funding. This position is part of the Preventive
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and compare material intralogistics handling alternatives—such as in-pit crushing & conveying, trolley-assist systems, and battery-electric trucks—in strip mining operations. This research is part of
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Ref.: 532732 Work type: Full-time Department: Centre for Information Technology in Education within the Faculty of Education (10001) Categories: Senior Research Staff & Post-doctoral Fellow Full
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to work independently, take initiative in moving a research project forward, and effectively manage time to meet deadlines in a remote environment Desirable qualifications: Strong data management, analysis