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Field
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-sectoral design workshops in collaboration with project partners. Develop and deploy AI-enhanced visualization tools and digital dashboards to support participatory engagement. Integrate environmental
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managing experiments using GPUs Ability to visualize experimental results and learning curves Effective inter-personal and team-building skills Self-motivated with an ability to work independently and in a
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related field. You have an excellent academic track record in topics relevant to robot perception - visual inertial odometry (VIO), mapping (SLAM) and 3D reconstruction. Experience with ultra-sound would be
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international conferences Create visualizations and infographics to communicate complex results to diverse audiences Write technical reports and policy briefs for stakeholders and funding agencies Contribute
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research and excellent digital literacy Strong interest in historical data, machine learning, data visualization, or digital hermeneutics Strong communication skills in English and good knowledge of French
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, Computational Social Science, Big Data. Relevant skills could include statistical analysis, data management and collection, causal inference, network analysis, graph theory, visualizations, and online tool
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programming languages and tools commonly used for medical systems integration and visualization (e.g., Python, C/C++, MATLAB, LabVIEW). Duration and Compensation This is a full-time appointment, with
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interpretable visualizations. Collaboration and dissemination: work closely with clinicians, biologists, and computational scientists; publish findings in high‑impact journals and present at international
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using UCINET software or coding in R. Writing and Presentation Development Synthesizing data from multiple sources to communicate findings via written, visual (i.e. sociograms), and multimedia displays
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; The ability to plan and conduct biological experiments and visualize results; Knowledge in the areas of transport biochemistry, molecular biology, working with plant in vitro cultures, protein sequence analysis