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data-driven methods to understand, design, and optimize complex energy systems and devices. Example topics include physics-informed machine learning, digital twins for turbines and reactors, AI-driven
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between established and early-career researchers in Germany and around the world ( https://www.physik.fu-berlin.de/forschung/dahlem-center-for-complex-quantum-systems/index.html ). The center’s
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Where to apply Website https://emploi.cnrs.fr/Offres/Doctorant/UMR5672-DAVCAR-002/Default.aspx Requirements Research Field Engineering Education Level Master Degree or equivalent Research Field Physics
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/bandi-di-concorso/bandi… Requirements Additional Information Eligibility criteria - Competencies in statistical physics and complex systems modelling; - Familiarity with population dynamics and
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accommodate family circumstances will be considered. Candidates will have a background in mathematics or physics and a record of outstanding research in the mathematical theory of Complex Systems
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transport Develop concepts to efficiently and actively cool LPA targets, with a focus on long-term stable operation In this context, perform complex multi-physics simulations, including heat transport
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learning / AI is highly desirable Prior exposure to nuclear physics data, detector systems, or scientific instrumentation is an advantage but not required Interest in interdisciplinary research
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Physics”, “Photonics”, and “Nonlinear Physics, Complex Fluids and Biophysics”. They cover a broad range of fundamental and applied research combining theoretical, computational and experimental
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to biological systems. Research topics therefore range from complex systems to living tissues, and from liquid crystals to foams, including polymers and granular systems. These studies lie at the
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what do we offer? Our group studies complex and biological systems with methods from physics in order to obtain a fundamental understanding of the complex phenomena that can emerge. Our theoretical