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provable guarantees AI-based cybersecurity: applying learning and AI-assisted techniques to network security, e.g., automata learning from security logs, validation of protocol models, and verified defensive
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, an ARIA-funded collaboration between EPFL and Imperial College London, aims to build a formally-verified ML inference engine, demonstrating that AI can help make verified systems competitive with unverified
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using machine learning approaches to uncover principles of cellular state transitions. The work will be carried out in close collaboration with other labs at EPFL, offering a uniquely rich environment
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with motor impairments. Please visit the .NeuroRestore website www.neurorestore.swiss to learn more about our mission. Main duties and responsibilities Supporting .NeuroRestore researchers and clinicians
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by Prof. Marc Gruber, within EPFL's College of Management of Technology. You will have scope to develop your own research agenda and to collaborate with Prof. Gruber and the Chair's researchers
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research is built around three intertwined questions: how to measure and understand behavior with AI, how brains and embodied agents learn to control the body, and how the brain builds a sense of its body
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, including compute, storage, and AI platforms, while working closely with researchers and IT teams across EPFL. This role requires a customer-oriented mindset, adaptability, and strong collaboration skills
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on developing new generative modeling approaches, scalable training algorithms, and foundation model technologies. The role is suited for candidates with a strong machine learning background who are excited
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positions cover the full stack of biological foundation model research: from core architecture design and pretraining at scale to integration into agentic interfaces. Both roles involve close collaboration
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proactive, organized, and motivated individual who enjoys working independently while collaborating closely with others. The ideal candidate is comfortable organizing daily experimental work from agreed