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The Path to Power: 2024 project utilises the unprecedented opportunity of more than four billion people voting in elections in 2024 to generate a comparative picture of the contemporary state
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of the award, awardees will be considered for Assistant Professorship. Awardees will also be assigned a faculty mentor for the duration of the scheme. Application Process Applications are open throughout
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studies linking preclinical discoveries to clinical trials in radiation oncology. Innovative imaging and biomarker development to track response to ultra-high dose rate therapy. The postdoctoral scholar
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level of English Advantageous: Experience nanomedicine. Active matter, in vivo imaging. Competencies and Skills: We value not only technical expertise but also the demonstration of core competencies such
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Postdoc in Extracellular Vesicles as Mediators of Gut-Microbiome Interactions in Parkinson's Disease
to ileostomy samples, Parkinson’s disease cohorts, and novel hydrogel/motility models. This approach allows us to reveal microbial processes that are difficult to capture with standard models, connecting patient
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access to data from AIMS-2-TRIALS, the world’s largest multimodal, longitudinal autism study; the South African BONO cohort, and the SLAM Image Bank, one of the world’s largest, real-world imaging/clinical
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High Performance Computing. Expertise in image and spatiotemporal data processing. A strong publication record in peer-reviewed journals and conferences. Excellent written and oral communication skills
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-up (Bruker dimension icon), and has further access at QMUL to SEM and TEM. We offer competitive salaries, access to a generous pension scheme, 30 days’ leave per annum (pro-rata for part-time/fixed-term), a
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models related to modern data management challenges (e.g., query feasibility, data correlations, probabilistic evaluation, scalability). Prototype and evaluate data system components or extensions
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ecosystems in a human transformed landscape” funded by the National Science Centre. Principal Investigator: prof. dr hab. Andrzej M. Jagodziński Key words: hyperspectral imaging, laser scanning, remote sensing