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Vacancies Postdoc position on Federated/Continual Learning for Time-Series IoT Data (TRUMAN Project) Key takeaways In this role, you will address the intricate challenge of enabling AI to learn
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and Digitisation in Apeldoorn, and the Kenniswerkplaats Onbegrepen Gedrag at Erasmus University Rotterdam. You will play a central role in working with the partners to get relevant information and
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, community-driven research software. Both institutions provide a full-time position each for the duration of 1 year, and both candidates will closely collaborate with each other and with data researchers in
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. Collaboration & Mentoring: Work closely with the project’s EngD researcher, providing the LES-generated data and expertise needed for the development of LiDAR-assisted forecasting methods. Methodological
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empirically grounded insights and strategies to support trustworthy data exchange and effective collaboration in emerging DPP ecosystems. The position offers the opportunity to conduct high-impact research
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in confined polymer systems. (Synthesis of complex polymer architectures will primarily be carried out by the partners in Dresden.) Information and application Interested? Send your application before
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technologies, and large-scale data infrastructures are transforming social practices, roles, institutions, and the frameworks through which people interpret and evaluate moral life. Existing ethical approaches
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droplet impact performance in the laboratory. - Implement droplet size dependent and impact velocity dependent cumulative damage models in a digital twin based on meteorological data for site
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environment comprising over 70 scientists working in photonics. Information and application Are you interested in this position? Please send your application via the 'Apply now' button below before June 30
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models. Using the acquired RF data, you will track microbubbles as they travel through the vessel phantom and bind to the vessel wall, and analyze changes in echo amplitude and spectral content associated