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University professorship (m/f/d) in 'AI in Occupational, Social and Preventive Medicine' (salary gra
implementation of AI algorithms and tools for analyzing and predicting health-related events, process optimization and decision support in healthcare. Validation of models to ensure accuracy and reliability
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hours per week), based in Berlin. Your Tasks Development of software for the analysis, management, and interpretation of omics data Selection and benchmarking of algorithms, libraries, and tools
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detectors (Partial) automation of detector characterization for more efficient analysis Algorithm development: Development of a correction method based on information field theory for atmospheric image
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multi-parameter ion-beam tuning procedures (collaboration with Univ. of Vienna and HZDR) and developments of machine learning (ML)-algorithms for optimization of beam parameters and control of relevant
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control, state estimation, and path planning algorithms for single and multi-agent robotic systems (UAVs). develop and train AI models for practical applications such as real-time object detection and
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applications. Our overarching aim is to obtain a holistic view of interconnected biological systems in health and disease. We develop clearing technologies for cellular-level imaging and deep learning algorithms
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terrestrial system models, for example using data analysis methods, such as data assimilation, physical- or process-based machine learning, or deep learning algorithms Analysis of the effects of human
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Required Qualifications: Bachelor's or master's degree in computer science, software engineering, or a related field Proven experience in technical leadership roles on cloud-native or distributed system
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simulation of complex detection systems, data handling and distribution. Good spoken and written knowledge in English and at least basis knowledge in German. Skills in organization and communication. We offer
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Master Thesis - Development of ligand conjugated lipid nanoparticles for targeted T cell delivery...
holistic view of interconnected biological systems in health and disease. We develop clearing technologies for cellular-level imaging and deep learning algorithms (AI) to analyze large imaging and molecular