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candidate in their doctoral research; Develop a network of academic and non-academic partners for the purpose of developing grant proposals; Support and/or coordinate grant proposals in collaboration with
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https://www.academictransfer.com/en/jobs/360185/postdoc-in-meta-science/apply/ Requirements Specific Requirements Motivated researcher, with a PhD in meta-science, science of science, science and
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postdoc to study how supply chains can stay resilient and meet regulatory demands, using system modeling and scenario analysis. Job description Supply chains are increasingly exposed to complex and
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, and climate projections depends critically on the adequate representation of land-atmosphere (L-A) feedbacks. These feedbacks are the result of a highly complex network of processes and variables
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: This postdoctoral position is part of an innovative research project in the field of soft robotics, aiming to design inflatable flexible robotic systems capable of safely interacting with complex or confined
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from control theory, machine learning, optimization, and network science, spanning diverse application domains such as energy systems, biomedical systems, neuroscience, and safety and security
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Inria, the French national research institute for the digital sciences | Montbonnot Saint Martin, Rhone Alpes | France | 7 days ago
representing mobility flows and EV trajectories from the collected data. • Redesign the model to incorporate more complex, nonlinear trajectories by removing constraints from the initial bipartite graph
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nationalism as a complex human phenomenon whose functions and intensity shift and vary over time. Rather than treating nationalism solely as a political ideology, we analyze its practical operations and its
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. AI4GI develops tailor-made neural network architectures, including sparse and biologically informed models, to predict disease risk and complex quantitative traits from large-scale genomic data such as
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signaling cascades that are integrated through dynamic and context-specific networks driving the cellular responses. Given the complexity and dynamic state of signaling networks, the current understanding