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University of North Carolina at Chapel Hill | Chapel Hill, North Carolina | United States | about 18 hours ago
tasks, including literature review, designing analysis to meet research objectives, and data analysis and visualization, including spatial and statistical analyses. The datasets are large and complex, so
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the HvA lectorates Responsible IT , Civic Interaction Design , Crossmedia , and Visual Methodologies . The AI, Media & Democracy Lab focuses on how AI and digital technology are transforming media and
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include statistical analysis, data management and collection, causal inference, network analysis, graph theory, visualizations, and online tool development. Experience in conducting online controlled
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, TensorFlow) with several years of practice Experience in maintaining high-quality code on Github Experience in running and managing experiments using GPUs Ability to visualize experimental results and learning
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Worldwide R&D Projects. Previous experience in one or preferably more topics from these areas is considered a merit: -Risk-aware navigation strategies that integrate visual-language models for autonomous
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for estimating benefits of these practices using the huge amount of data generated from this project. -Support projects on the development of digital twin systems, models, and user interfaces for visualizations
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thinking skills. Competence in data analysis and visualization using software such as GraphPad Prism, R, or Python. Excellent scientific writing and communication skills, with a track record of peer-reviewed
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in bioinformatics analysis and data visualization of our ongoing research projects on molecular characterization at the mRNA, miRNA, proteome and metabolome level from multiple lung compartments. Our
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(e.g., R, Python, MATLAB) demonstrated ability to translate complex scientific results into clear written, oral, and visual outputs ability to independently lead research while critically reflecting
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Develop and implement data visualization tools to communicate results to stakeholders Collaborate with other members of the research team to integrate genomics and phenomics data and develop new approaches