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Your Job: Synthesis and physicochemical characterization of energy materials or representative model systems Characterization of the dynamical and structural properties of energy materials with a
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required. Access to such high-energy X-rays enables larger penetration depths and the investigation of materials under highly absorbing or extreme conditions. Achieving these capabilities is essential
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working time models, including options close to full-time ( https://go.fzj.de/near-full-time ), allow you to tailor your working hours to suit your individual needs FAIR REMUNERATION: Depending on your
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volume correlation processing of images in preparation for image-based modelling Your profile PhD in physics, materials science, computer science, applied mathematics or a related field strong background
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competitive research in AI-driven semantic analysis and automated reasoning-flow modeling, with applications to educational materials, scientific documents, and research authoring. Your work will focus
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technologies for batteries. Your tasks in detail: Develop innovative quantum computing approaches for the simulation of electrochemical processes in complex electrode materials Connect quantum-enabled models
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organize soft and fluid-like material. They currently focus on the organization principles of liquid droplets in biological cells, but they are also interested in broader questions in biological physics
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, effort, and experimental expenses, and to provide data that is unachievable through experiments. Chemical kinetic models form the basis for a predictive tool, used to understand, optimise, and engineer
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-XRF, Raman, FTIR in reflection mode) to enable multimodal data fusion and automated material characterization. • Apply and further develop machine-learning and statistical models (e.g. PCA, SAM