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Field
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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
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Environment (VTE) for disaster response simulation, integration of Building Information Modelling (BIM) with Structural Health Monitoring (SHM) using smart sensor networks, and resilience-informed design
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Environment (VTE) for disaster response simulation, integration of Building Information Modelling (BIM) with Structural Health Monitoring (SHM) using smart sensor networks, and resilience-informed design
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for analysis of the data you create. Your findings will be a vital part of understanding the evolution of cancer drug resistance in cell models and in patients. About you: You’re excited about our research
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Leibniz-Institute for Plant Genetics and Crop Plant Research | Neu Seeland, Brandenburg | Germany | 6 days ago
have hands-on experience in crop genomics and managing genotyping data. You bring first experience with biostatistics methods, e.g. with mixed-models. You are familiar with data analysis using
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amphibians and other aquatic vertebrates. Using advanced imaging, neurophysiological, and molecular biological methods, we investigate the olfactory system. Furthermore, we use the olfactory network as a model
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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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Max Planck Institute for Dynamics of Complex Technical Systems, Magdeburg | Magdeburg, Sachsen Anhalt | Germany | 3 days ago
to understand the reaction mechanisms and stir the selectivity towards hydrogenated N-forms, while suppressing the formation of undesirable products Detailed modelling, simulation and optimization
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on the following tasks with either with a stronger model-development or application focus: Design knowledge-graph-augmented transformers and retrieval-augmented generation (RAG) pipelines that enable
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scientists on, e.g.: Developing self-supervised learning frameworks to extract features from unlabeled high-resolution microscopy data Training and evaluating segmentation models for detecting and