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at the atomic scale, using density functional theory-accurate machine-learned potentials and molecular dynamics simulations, in close collaboration with leading European research institutes and steel industry
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postdoctoral appointment in Remote Sensing of the land surface, with a strong interest in the integration of geospatial Artificial Intelligence (AI) and machine learning. Are you enthusiastic about the chance to
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the intersection of machine learning (ML) and the sounds of wildlife (“bioacoustics”). We are also happy to consider candidates in one of the two fields who can demonstrate a strong basis for working in this cross
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theoretical challenges motivated by astrodynamics, optimisation, control, scientific machine learning, mission design and autonomous systems, translating these into new research directions in deep learning
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the CLARA AI agent — bridging cutting-edge machine learning methods with empirical insights from the educational arm of the project. A central technical challenge guides this position: How can an LLM-based AI
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at the intersection of conversational AI, human–computer interaction, multimodal interaction, user modelling, and cultural heritage. As a postdoctoral researcher, you will: Conduct research on dialogic interaction
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substantial experience with machine learning techniques. You have experience with the PreFer data challenge. You have experience with working with Dutch register data. You have the ability to identify
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, solvent-based recycling process for complex plastic waste streams such as multilayer packaging and e-waste, while Exergy will develop the digital-twin and machine-learning tools that make the process
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packaging and e-waste, while Exergy will develop the digital-twin and machine-learning tools that make the process adaptive and scalable. The research effort will be directed towards the selective recovery in
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-quality datasets that are structured and annotated for simulation and machine learning. Develop Digital Twins and simulation pipelines for virtual validation and predictive performance assessment. Implement