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/Materials Science funded by ERC StG with excellent opportunities for both research and career development. About us Our research focuses on extracting and isolating bio-based polymers such as cellulose and
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computer vision in dusty conditions by incorporating hyperspectral cameras. In addition, assisting in project applications and general development duties of the Chair. The position is available from
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to be developed. One promising research direction is the use of physics-informed deep learning, such as physics-informed neural networks or deep neural operator networks. Tasks: Work in a team on national
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regeneration in the forest interior“we aim to develop innovative remote sensing approaches to enhance the mechanistic understanding of the effects of increasing forest disturbances on closed canopy forests
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differential equations (PDE) in the model to describe either environmental influences or a more detailed component behavior offers a possible solution to this challenge. The goal of the project is to develop
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PhD position in interpretable machine learning for dementia prediction. The project focuses on developing interpretable deep learning models for dementia prediction using multi-modal data, including MRI
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11.11.2024, Wissenschaftliches Personal In the project “BIG-ROHU” (BIG Data - Rotor Health and Usage Monitoring), a system is being developed which provides information on both the health and the
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solutions and development of criteria for focused design improvements on com-pressor rotor blades in the near-end wall region. We Offer You will be a part of an international working environment with a strong
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Design”, led by Prof. Ledendecker at the HI-ERN in Erlangen. The department specializes in the development of metal-based inorganic catalysts aimed at advancing the global energy transition. Our research
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information processors and how nuclei dynamics coordinate solving complex tasks. To this end you will perform fluorescence microscopy on nuclei populations and quantify their dynamics while challenging Physarum