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Field
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to work at high levels of accuracy Ability to present complex information effectively to a range of audiences Proven ability to analyse data and write-up results Experience of working collaboratively with
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research in the natural, mathematical and computer sciences with a focus on the processing, structuring, and analyzing of large amounts of complex data and the development of computational methods and
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forming fundamental challenges. Physics-based models are too complex, while pure data driven models lack explainability, ultimately reducing the robustness. The proposed solution is the development of a
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preclinical models and retrospective human MTLE datasets. Apply complex signal-processing approaches to analyze animal and human intracranial EEG. Develop and implement computational network analyses
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complex data and prepare high-quality research outputs and reports A developing research profile within the discipline or area of expertise A developing network of academic, industry and professional
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flow cytometry, mass cytometry (CyTOF), single-cell RNA sequencing, and T-cell receptor (TCR) repertoire analyses. Analyze complex immunological datasets using FlowJo, R, RStudio, and other statistical
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Biology demonstrated by good research track record Familiarity with SAXS methods and data analysis Relevant experience with data collection, processing and data analysis for complex multidimensional NMR
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complex environmental datasets. Knowledge, Skills & Abilities: Advanced knowledge of physical oceanography, geophysical fluid dynamics, numerical methods, or closely related principles relevant to physics
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research fellow to lead the computational arm of a Leverhulme-funded project investigating how cryogenic OrbiSIMS interacts with complex biomolecular structures. Working closely with experimentalists and
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HAICu project to help unlock the potential of cultural digital archives through multimodal use, providing richer context and a more comprehensive analysis of current complex issues in society. If