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Field
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with a strong background in applied mathematics, control theory and/or optimization to apply for a fully funded 4-year PhD position in the Smart Manufacturing Systems (SMS) group at the Engineering and
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Framatome's Research Center (DTI). **PhD Programme** The objective of this PhD research is to develop a wear model capable of predicting wear kinetics under variable impact-fretting loading conditions for a
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contribute to the development of predictive human in vitro models for ageing research while providing robust alternatives to animal experimentation. Where to apply Website https://emploi.cnrs.fr/Offres
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proteomics Bioinformatic data integration and development of predictive biomarker models Clinical validation of findings using patient cohorts from both institutions Regular scientific exchange and
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, process intensification, and hydrogen yield optimization. These interconnected phenomena require predictive modeling tools capable of supporting the scale-up from laboratory to industrial operation [3–5
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System Model, vesion 3 (NorESM3), and a central satellite dataset for EEI is from the Clouds and the Earth’s Radiant Energy System (CERES). The specific tasks intended for the PhD fellow are to (i) Analyze
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pipeline with fundamental discovery science. Where to apply Website https://ibb.edu.pl/en/phd-studies/rekrutacja/ Requirements Research FieldBiological sciencesEducation LevelMaster Degree or equivalent
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Research Center for Molecular Medicine (CeMM), ÖAW | Vienna, Virginia | United States | about 2 months ago
and modeling of RESOLUTE data (https://re-solute.eu/ ) together with metabolic, structural, genetic and clinical datasets to generate new insights into transporter biology: how cells regulate access
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interpretation and prediction of structure-property relationships. https://sustainablepolymersynthesis.com/ Interested? Want to know more about this position or what it’s like to work at our university? Reach out
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robust optimization integrated with advanced adversary models and control frameworks such as model-predictive control or reinforcement learning. The exact details of the project will be decided in a