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Field
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remove the influence of specific data from trained models becomes critical. Yet, despite the EU’s General Data Protection Regulation (GDPR) enshrining a “right to be forgotten”, current federated learning
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Inria, the French national research institute for the digital sciences | Villers les Nancy, Lorraine | France | 17 days ago
Website https://jobs.inria.fr/public/classic/en/offres/2026-09928 Requirements Skills/Qualifications Profile: - The candidate is completing a Master's or engineering’s degree in Computer Vision, Electrical
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modelling and oomph-lib for continuum mechanics simulations, enabling the integration of discrete and finite element methods. Coupled with machine learning techniques, this approach will address the complex
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industries like pharmaceuticals, food processing, and construction, the project may also incorporate machine learning methods for model calibration and optimisation, driving more sustainable material handling
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an individual with a disability, military or veteran status, genetic information, or other protected classes under the law. For additional information please see the University's Notice
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, gender, gender identity or expression, national or ethnic origin, shared ancestry, age, status as an individual with a disability, military or veteran status, genetic information, or other protected
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3 Apr 2026 Job Information Organisation/Company Tampere University Research Field Computer science » Programming Computer science » Other Engineering » Computer engineering Engineering » Other
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developing human-like intelligence. For both scientists and the broader public, an urgent question is “How smart is AI currently and how intelligent will it become?”. However, we do not know because current
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electric double-layer capacitors (EDLCs). However, their synthesis remains largely empirical, with limited predictive understanding of how processing parameters control pore structure and electrochemical
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aspects of machine learning focusing on efficiency, generalization, and sparse neural networks. Currently we are expanding our expertise by applying our theoretical findings also to robotics. Hybrid is our