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genomic changes. In this role, the successful applicant will have the opportunity to participate in the analysis and interpretation of multi-omics datasets including whole genome sequencing, bulk and single
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Engineering and a strong background in experimental magnetism. The position, based within Prof Jason Robinson's research group at the Department of Materials Science & Metallurgy, is part of the project
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/bioinformatics, and data science. Work Performed · Work in highly collaborative inter-disciplinary environment with clinicians, econometricians, statisticians, and data scientists · Lead statistical analysis
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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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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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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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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
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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