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Field
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-driven materials modelling, digital research workflows, and multiscale integration for Waste-to-Value energy conversion systems. As a PhD in AIM, you will help build the first ab initio–based Digital Twin
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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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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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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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objective is to develop methods that move beyond correlation-based prediction toward causal reasoning, intervention-aware modelling, and interpretable AI systems. This transition from correlation to causation
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the world, we work together to develop solutions for the global challenges of today and tomorrow. Where to apply Website https://academicpositions.com/ad/eth-zurich/2026/phd-position-in-cryogenic-carb
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the next generation of intelligent wireless systems. Where to apply Website https://www.academictransfer.com/en/jobs/362604/phd-in-hybrid-rf-and-optical-wi… Requirements Specific Requirements A master’s
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SD-26109- POSTDOCTORAL RESEARCHER IN AI-BASED ENERGY MANAGEMENT OF RESILIENT MICROGRIDS WITH SECO...
simulation models of microgrids, second-life battery systems, solar PV generation and critical community loads. Validating the proposed control strategies using real-time simulation and hardware-in-the-loop
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traffic demands increase, there is a growing need for innovative methods to continuously assess track condition and predict deterioration. This PhD project addresses this challenge by developing a novel