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-Euclidean spaces Scalable layout methods and visual analytics for large and dynamic networks Dimensionality reduction and embeddings for visual exploration Interaction design and user-centered evaluation
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, or a related discipline Interested in climatology/meteorology as well as quantitative methods Prior experience in programming is a plus (e.g., using R or Python) Good communication skills and a high
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processing and machine learning methods, and big data analytics solutions to extract highly accurate large-scale geo-information from big Earth observation data. Our team aims at tackling societal grand
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: Completed master studies in the field of environmental sciences, forestry, landscape ecology, remote sensing or related fields Interested in remote sensing, quantitative methods and programming Prior
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knowledge of quantitative methods, particularly in statistics and econometrics; experience in machine learning is a plus Background in business/management/behavioral science Experience with programming
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are pursued by this Center: (1) develop a new set of consistent scientific methods for mobility planning and management, (2) integrate a new set of modular metrics for responsible mobility, (3) embed
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these materials into high-performance fibers and functional materials. By manipulating molecular interactions through chemical and physical methods, we tailor the structural and mechanical properties of bio-based
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university Heidelberg (Prof. Dr. Skyler Degenkolb) seek to bring quantum sensing methods into precision neutron science, further extending the power and reach of these measurements. Innovative new devices can
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space. We quantify these changes, identify their causes and describe their impacts on biodiversity and ecosystem ser-vices. To do this we use a combination of diverse methods, from empirical research
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scientists develop next-generation imaging and sensing methods to measure previously inaccessible properties of living systems, hence, catalyzing breakthroughs in biology, medicine and the environment