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Inria, the French national research institute for the digital sciences | Montbonnot Saint Martin, Rhone Alpes | France | 1 day 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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Max Planck Institute for Solar System Research, Göttingen | Gottingen, Niedersachsen | Germany | 12 days ago
turbulence are fundamental problems in geophysical and astrophysical fluid dynamics. This project will focus on understanding the nonlinear dynamics of rotating flows and turbulent transport, with applications
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will work with Professor Peter Hintz on problems in the areas of geometric partial differential equations and general relativity. These include: linear and nonlinear stability problems and scattering
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representative microstructures or using an equivalent homogenized material model. The project therefore combines multi-scale modeling, large deformations, nonlinear viscoelasticity, and transient dynamics
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for a millimetre-wave metasurface project using nonlinear circuits such as diodes. This position may require travel to these partner organizations. To be considered, the candidate is expected to have
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of biological and statistical physics. Candidates for the position must have a PhD in physics or a related discipline, preferably with expertise in stochastic processes, nonlinear dynamics, and control theory
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technology at high repetition rate in new wavelength ranges, with the help of multi-pass cells, novel nonlinear devices and pulse/beam shaping. Work duties The main duties involved in a post-doctoral position
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The Max-Born Institute for Nonlinear Optics and Short Pulse Spectroscopy (MBI) conducts basic research in the field of nonlinear optics and ultrafast dynamics arising from the interaction of light
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flexibility to choose research projects and mentor(s) among the faculty members in the department. Possible research areas and related desired background consist of: Research on the dynamics of nonlinear
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of artificial intelligence, multi-omics data integration, and functional genomics, aimed at predicting synthetic lethality in cancer - including representation learning, nonlinear embeddings, and predictive