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Field
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play a central role in this interdisciplinary initiative. They will: Develop and apply machine learning (ML) methods – including surrogate modeling, feature extraction, and inverse design algorithms
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. Furthermore, we use the olfactory network as a model to study the dynamics of neuronal development, synaptogenesis, neuronal degeneration, and regeneration. Our research is complemented by behavioral studies
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Virtual Training Environment (VTE) for disaster response simulation, integration of Building Information Modelling (BIM) with Structural Health Monitoring (SHM) using smart sensor networks, and resilience
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(defect) structures and activity/selectivity are studied by combining variety of spectroscopic techniques. Controlled synthesis and nanoscale structuring using atomic layer deposition enable the design of
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, 65 %). The Institute of Pharmacology focuses on deciphering the molecular mechanisms that control regeneration as well as tumor initiation and progression in epithelial tissues. The PhD project aims
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%). The Institute of Pharmacology focuses on deciphering the molecular mechanisms that control regeneration as well as tumor initiation and progression in epithelial tissues (https://www.uni-marburg.de/en/fb20
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, 65 %). The Institute of Pharmacology focuses on deciphering the molecular mechanisms that control regeneration as well as tumor initiation and progression in epithelial tissues (https://www.uni
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excursions. The PhD student will work on analysing the reliability of paleomagnetic records, deriving uncertainty estimates, and building time-dependent models of the paleomagnetic field evolution using a
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language models (LLMs) Proficiency in Python programming and confident use of Unix/Linux environments; ideally experience with version control systems (e.g., Git) Interest in or experience with semantic web
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features from unlabeled high-resolution microscopy data Training and evaluating segmentation models for detecting and characterizing defects such as dislocations Applying generative models (e.g., GANs