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of medieval Latin. Excellent scientific writing skills, with a high production rate. Minimal comfort with computer tools and quantitative methods. No technical expertise is required, but a minimum level of
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SUSMAT-RC - Postdoc Position in Computer-Aided Design and Discovery of Sustainable Polymer Materials
candidate is expected to: Build and evaluate chemical databases based on experimental and computational data. Establish predictive models based on artificial intelligence methods. Utilize the developed models
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hyperparameter optimization and conformal prediction methods; The online monitoring of model reliability and performance indicators in dynamically changing environments; The integration of synthetic data from
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additive manufacturing—to component-level behavior and overall engine system performance using state-of-the-art MBSE methods and tools. Particular attention will be given to how manufacturing-enabled design
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/RFSoC boards, generating synthetic training datasets and extracting robust features for SIGINT and spectrum‑monitoring pipelines Develop and integrate TDOA/FDOA‑based geolocation methods into RF
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estimation of adverse Zika outcomes while addressing measurement biases. We aim at generating evidence to inform public policy, healthcare providers and pregnant individuals, improving prevention during
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concrete (corresponding to 40% of cement use) and CEM I cement, leading to inaccuracies in estimating CO₂ capture, especially for other cement-based materials and modern blended cements. This project will
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Deutsches Zentrum für Neurodegenerative Erkrankungen | Bonn, Nordrhein Westfalen | Germany | about 2 months ago
research interest of PRECISE lies in the establishment, application and improvement of single-cell OMICs methods in the areas of neurodegeneration and immunology. For more general information, please also
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throughput genomics that informs advanced numerical analysis methods (modeling, statistics, machine learning). Plankton encompasses all organisms roaming with marine currents. Those organisms are responsible
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processors. The candidates will contribute to topics including: The offline and online calibration of learning systems through methods such as conformal prediction, hyperparameter optimization, and reliable