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geometries and process-induced defects demand new inspection approaches. The project combines modelling, sensor fabrication, experiment, and data analysis. You will work with a team of experts to develop
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methods to understand and predict the adsorption, self-assembly, and protective behavior of N-heterocyclic carbenes (NHCs) on metallic and oxidized surfaces. NHCs are promising corrosion-inhibiting
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, predict, and manage them remains fragmented across disciplines. The Understanding and Predicting Impacts of Climate Extremes under Global Change Doctoral Network (CLIMES DN) (https://www.climes.se/climesdn
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constitute the core objective of the proposed PhD project. Expected contributions of the Thesis Model realistic multi-orbit/multi-operator SatCom scenarios; Design AI/ML-based prediction models for mobility
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materials databases to be integrated into the NIST-JARVIS (https://jarvis.nist.gov/ ) infrastructure. We work closely with experimental collaborators for validation and focus on releasing software, models
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and increased uncertainty in life and non-life insurance modelling. data-driven prediction of insurance premiums and associated quantification of uncertainty. Qualifications and personal qualities
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for predictive modeling scenarios, causal modeling is also within the scope of the position. The position is embedded in the ten-year gravitation grant Stress in Action, funded through NWO (Dutch National Science
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highly motivated PhD student to develop advanced models for predicting the fatigue life of additively manufactured steel in nuclear reactor water environments. The project focuses on modeling corrosion
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of Robotics and Industrial Informatics (CSIC-UPC) offer a position to work on World Models for Human Behaviour Anticipation https://ramonllull-aira.eu/archivos/theme_field/world-models-for-human-behaviour
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education setting and a working knowledge of higher education regulations and policies Experience in advanced data analysis, predictive modeling, and leveraging data to drive strategic decision-making