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workflow for the analysis of single-crystal diffuse scattering. In this project, you will have the opportunity to contribute towards reaching this challenging aim. Your tasks include: Deducing numerous
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variables, both historic and future, is also an essential ingredient to move past the rear-mirror approach of standard classical forecasting methods. The project will focus on the use of transformer based
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Engineering, or a related discipline with substantial background in fluid mechanics. Essential skills: • Strong knowledge of numerical methods and fluid mechanics • Experience with scientific
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, ultimately optimising the deposition process. Additive manufacturing (AM) is a rapidly advancing technology, driving numerous innovations and finding diverse applications across industries such as aerospace
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to the development of non-destructive methods to monitor natural degradation, using advanced analytical and statistical approaches. • Develop, implement, and refine models that integrate micro-environmental
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methods from building physics, you will bridge the gap between room-scale dynamics and micro-environments of documentary heritage objects, translating complex simulation data into actionable conservation
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To strengthen our team in the division “Acoustic and Electromagnetic Methods” in Berlin-Steglitz, starting 01.04.2026, we are looking for a PhD student (m/f/d) in the field of physics or engineering
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, or geometric deep learning. Experience with optimization methods, numerical modeling, or simulation of complex systems. Experience with 3D modeling, CAD APIs, or computational geometry is an advantage
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systems. By combining microclimate modelling, remote sensing data, and data-driven methods, the results are integrated into a Digital Twin framework. The research will support predictive risk assessment and
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with optimization methods, numerical modeling, or simulation of complex systems. Experience with 3D modeling, CAD APIs, or computational geometry is an advantage. Experience and abilities