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, scientific computing, and optimization). These full-time 9-month temporary positions are renewable twice depending on, as applicable, satisfactory teaching performance and research progress, for a total of
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mathematics with a preference for candidates who specialize in nonlinear optimization, the mathematics of machine learning, or stochastic modeling. The faculty member in this position will teach mathematics and
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experimental constraints associated with the use of very short focal lengths to achieve ultra-high laser intensities. The first objective of the PhD project will be to determine the optimal parameters
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positioned team of experts in the field of photonic components, laser sources, and nonlinear converters. You will contribute to the improvement of fiber components and new designs. You will independently work
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nonlinear behavior makes it difficult to guarantee safety and stability. How can we exploit the expressive power of machine learning without compromising the rigorous guarantees required in safety-critical
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. The objective will be to determine the optimal correction strategies as a function of tissue type and imaging depth. A second objective will be to exploit this platform for organ-scale mapping of intrinsic label
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on developing the low-dimensional nanophotonics, focusing on the near-field, nonlinear and quantum optical properties of emerging low-dimensional materials. The researcher will work on a project focused on the
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differential equations, mathematical modeling, nonlinear optimization, and applied mathematics in general. ● Payment according to the collective agreement for the public service (TVöD Bund) including the usual
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Facility is seeking a scientifically oriented and technically capable postdoctoral researcher to contribute to the operation and further development of its High Harmonic Generation (HHG) Beamline
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for stochastic, distributionally robust, and mixed-integer nonlinear optimization problems. The successful candidate will conduct research at the intersection of stochastic programming, optimization under decision