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Systems Design, Analysis and Testing, (3) Laser Diagnostics and Sensors in Hypersonic and Extreme Environments, (4) Mathematical Foundations of AI, Uncertainty Quantification, and Reduced Order Modeling
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to apply Website https://www.academictransfer.com/en/jobs/357846/post-doctoral-researcher-digita… Requirements Specific Requirements Responsibilities and tasks: Employment of state-of-the-art tools to run
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targets the development of advanced grey-box modeling frameworks for multiphase flow systems, combining mechanistic, multi-scale flow models with data-driven inference and uncertainty quantification
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targets the development of advanced grey-box modeling frameworks for multiphase flow systems, combining mechanistic, multi-scale flow models with data-driven inference and uncertainty quantification
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of artificial intelligence and scientific computing including physics-informed neural networks and digital twins; uncertainty quantification, high-dimensional data analysis, and visualization; generative models
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networks, risk analysis or uncertainty quantification (preferred). Knowledge of data science in general as well as practical experience with conducting data science analyses with good programming skills
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two real-world care pathways using existing data and gold-standard LCA methods; supervising PhD candidates working on the quantification of environmental impacts in healthcare; contributing to peer
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strong focus on (deep) machine learning are: Trustworthy and interpretable AI with uncertainty quantification Detection and characterization ofsub-visible particles in microscopy images
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, etc.) development of predictive models and digital decision-support tools for nutrition and health method development in causal inference, integration of heterogeneous data sources, uncertainty
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design and evaluation of uncertainty quantification methods, as well as the integration of geostatistical techniques with Machine Learning models, analysing their reliability in fisheries and environmental