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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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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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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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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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of Singapore, and EPFL (Switzerland). These partners are looking for talents in several domains of machine learning, AI, computational biology, and biology, to develop PhD theses across the main pillars
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adaptability at the product-scale through material science and design. Main duties and responsibilities As a research collaborator, you will be expected to: Conduct cutting-edge research including experimental
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and associated environmental impacts. Contribute to short-term (2026 to 2030) and long-term (2030 to 2050) verticalisation forecasting models based on machine learning, and to their validation against
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Finance at EPFL seeks postdocs to reinforce our research in quantitative finance with a focus on applied machine learning. Main duties and responsibilities Working and collaborating on research projects
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an opportunity for close collaborative work. Main duties and responsibilities You will develop an acquisition and reconstruction framework that exploits sparsity of the underlying dynamics and microchip sample