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Are you passionate about the future of circular manufacturing and intelligent quality control? Join us to develop AI-powered frameworks that improve real-time decision-making in additive
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PhD on 2D quantum photonics : towards neuromorphic applications with 2D ferroelectrics materials M/F
nanophotonics with 2D materials. We offer a unique opportunity to explore emerging phenomena such as sliding ferroelectricity, ultra-low-threshold nonlinear photonics, and exciton engineering. The project is part
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high second-order and third-order nonlinearity, the former enables frequency doubling, electro-optical modulators (switches) and the latter enables optical frequency comb (OFC). More importantly, large
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nonlinear optics). The PhD student will acquire expertise in the field of water-soluble chiral nanoclusters, from individual nanoclusters to supramolecular nanoclusters, focusing on their photophysical
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create different chiral nanomaterials that will be studied by optical spectroscopy (circular dichroism, photoluminescence, circularly polarised nonlinear optics). The PhD student will acquire expertise in
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Identifying and validating models for complex structures featuring nonlinearity remains a cutting-edge challenge in structural dynamics, with applications spanning civil structures, microelectronics
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disciplines. Our areas of expertise include nanophysics, biophysics, nonlinear and condensed matter physics, few-body systems, nuclear and hadronic physics, high-energy physics, and astrophysics. We support a
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the other 14 PhD students in the doctoral network, including 3 training schools. As a participant of the project, the PhD student will become part of a team at DTU with expertise in nonlinear optics in
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for a full-time, time-limited, 12-month, non-tenure track Research Assistant/Associate/Full Scientist, in the area of nonlinear and adaptive control. Initial appointment is for one year, with
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and control with unprecedented sensitivity. You will carry out pioneering research at the intersection of two distinct areas of physics. You will develop a chip-based levitation system that can be