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Field
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areas in data science and engineering systems. Required Knowledge, Skills, and Abilities Demonstrated expertise in computational sciences and numerical modeling. Demonstrated expertise in machine learning
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. The postdoc will engage in linking these two aspects by numerical optical modelling, which is the cornerstone of the project, in order to promote this interdisciplinary research approach over the long term
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-preserving finite element methods, advanced solver strategies, multi-fluid systems, surrogate modeling, machine learning, and uncertainty quantification. The position comes with a travel allowance and access
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, Python, or C++ is required. A strong interest in numerical modelling, sound, signal processing and programming is expected. Additionally, very good command of German and English as well as experience with
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will involve applying multiple time-dependent electronic structure and nonadiabatic dynamic methods to model the CISS effect in molecular systems. Method development, potentially in the realm of time
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physics and condensed matter theories to address the problem of fracture in complex materials. You will be working with experimental model systems and numerical simulations of materials that exhibit
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Research FieldPhysicsYears of Research ExperienceNone Research FieldTechnologyYears of Research ExperienceNone Additional Information Eligibility criteria Creation of models Analytical calculations Numerical
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physics and condensed matter theories to address the problem of fracture in complex materials. You will be working with experimental model systems and numerical simulations of materials that exhibit
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Internal Number: JR90686 Position Summary This position will focus on integrating high-resolution field monitoring, remote sensing, and statistical and numerical modeling approaches to improve predictive
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, data assimilation, surrogate model design, and machine learning algorithms. The position comes with a travel allowance and access to advanced computing resources. The MMD group is responsible