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, subjective evaluations, and physiological data. Conduct field campaigns in buildings, including multi-domain monitoring and user-based assessments. Investigate visual and non‑visual effects of light on
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Assistant Professor position in Computer Science with a Focus on Interdisciplinary Data Science_3...
As part of expanding the Centre for Visual Data Science and the Centre for Digital Humanities, the Department of Mathematics and Computer Science at the University of Southern Denmark, Odense
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activities, including: Information gathering and sorting Data collection and registration (both manual and through web scraping) Text editing and formatting Designing graphical visualizations Proofreading and
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of you You have at least three years’ experience working in the areas above. The ideal candidate will have solid experience working with the following: Communication project coordination Visual
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. Documented experience with the collection and management of large datasets from instruments. Experience in general data handling and processing, including import, cleaning, filtering, and visualization of data
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markets. Additionally, the ability to develop clear and functional visualization dashboards is expected. The successful candidate should have experience or strong interest in the following areas: Real-time
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tools and platforms that simplify the visualization and analysis of complex experimental datasets. Provide consistent technical support, addressing challenges in a timely manner to ensure smooth day-to
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of technical knowledge, we expect you to have: A strong knowledge of R (strong skills in data wrangling using tidyverse syntax and functions, working with quarto documents, visualizing data, and writing clean
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testing and condition monitoring using modern machine learning, including multimodal foundation models and related data-driven and physics-informed approaches. Research topics may include visual and real
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Programming in Python, R, SQL, Java, or similar languages Spatial and spatiotemporal methods when relevant, including geo-visualization, spatial optimization, and spatially explicit modelling for sustainability