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29.04.2021, Wissenschaftliches Personal This PhD position is in the field of resource management for wireless network that leverage “digital twins” modeling aspects of the physical (such as user
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-performance technologies to investigate the complex interplay between the human organism and food ingredients. The research group Mechanoreceptors/ Section II at Leibniz-LSB@TUM is currently looking for a PhD
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highly motivated doctoral student to join an ambitious project aimed at building machine and deep learning models to study the genetics of human disease. Funded as part of the Helmholtz AI program, the
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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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teacher-student synchronization. However, this synchronization necessitates an exact student model, making the ACT often inexact and susceptible to uncertainty and variability. The project will aim
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quantification, model-order reduction, or multi-fidelity methods. The primary fields of application are life science, medicine and health, earth observation, and robotics. Consequently, a MUDS student will learn
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and organoid tissue culture models to study the LTM effects on inflammatory signaling and virus-induced carcinogenesis. Unique 3D-cell biology techniques as well as molecular biology techniques, such as
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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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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
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, Google.org, SAP, Merck, TUM Klinikum, Holtzbrinck). Diverse research topics and technologies, including: Conversational Semantic Search, Question Answering Systems, Complex Information Extraction. Fact