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Veterinärmedizinische Universität Wien (University of Veterinary Medicine Vienna) | Austria | 3 days ago
efficiently. To this end, we are looking for a senior researcher who will support the team in establishing techniques and technologies to visualize the data in an efficient and advanced way. Candidates should
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to the computational analysis of visual culture in the humanities. The postdoctoral researcher will work closely with the project PIs, Lauren Tilton and Taylor Arnold, to develop and implement educational resources
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position within a Research Infrastructure? No Offer Description Activities: This research investigates the use of artificial intelligence in developing data visualization systems for born-digital collections
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), combining state-of-the-art in vivo approaches with quantitative data analysis. About the lab and environment The Rebola Lab (https://therebolalab.org ) studies how variability in synaptic function across
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projects integrating omics, clinical and medical imaging data, contributing to biomarker identification and the development of computational approaches for healthcare. Key responsibilities include analysis
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the cloud. Implementation of pipelines to collect real-time data from IoT sensors. Expertise in IoT-oriented databases (e.g., InfluxDB, PostgreSQL, Firebase, etc.). Knowledge of data visualization tools (e.g
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) of the Croatian Science Foundation (hereinafter: HRZZ). Further information about the PDIP-2026 call is available on the Croatian Science Foundation website: https://hrzz.hr/prijava/otvoreni-natjecaji/ The Call is
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visual dimensions in the context of face, animacy, and object representations more generally. We collect and analyse human behavioural and brain imaging (fMRI and M/EEG) data. We also analyse macaque
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, processing, visualization, interpretation…) Analyze single-cell and spatial transcriptomics datasets Decipher metabolomic patterns Perform high dimensional data analysis and integrative ‘omic’ data analysis
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for the analysis of hyperspectral imaging data applied to pictorial layers, based on coupling physical radiative transfer models (two-flux and four-flux approaches) with machine learning methods. The researcher will