Sort by
Refine Your Search
-
Listed
-
Category
-
Country
-
Program
-
Field
-
fracture because they naturally accommodate wave propagation and avoid the repeated solution of large nonlinear systems. Yet, they are only conditionally stable, and the admissible time step is usually
-
from waveguides on the chip. By using the latest advances in electrooptic nonlinear materials, these waveguides can adjust the brightness and phase of the light at very high speed. The METAPIC project is
-
Astronomy , Neutrino physics , Neutrino physucs , Non-equilibrium quantum physics , Nonequilibrium physics in bulk and molecular quantum materials , Nonlinear and Complex Systems , Nonlinear Integral Systems
-
on advanced nonlinear optics and ultrafast laser techniques. The experimental work will be carried out on a table-top HHG beamline, producing XUV pulses with durations in the tens-of-femtoseconds range
-
optimization of nonlinear problems will be essential. The researcher must also be familiar with image manipulation and software development in Matlab or Python. The ability to collaborate both in academia and
-
support the research and development of a new generation of light source based on gas-filled hollow fibers. Despite the rise of novel nonlinear materials, the generation, control and application of light
-
in nonlinear X-ray-matter interactions and ultrafast diffraction/imaging are targeted with this position as Postdoc in the MID group. For our MID group, we are looking for a Postdoctoral researcher for
-
, nonlinear science, wave propagations in lattices, fluid mechanics and financial mathematics. About You The successful candidate will be expected to contribute to teaching and curriculum development
-
electricity markets; conducting research in nonlinear, convex, and mixed-integer nonlinear optimization; designing and implementing advanced computational and algorithmic solutions; performing computational
-
the complex multiscale nonlinear interactions at the origin of such extreme events. In this project, you will develop machine learning-based reduced-order models which can accurately forecast