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than 18,500 people, including over 14,000 students and 4,000 researchers from more than 120 different countries. Post-doc/Scientific collaborator - Bio- and Nano- Instrumentation 1 Mission The research focus
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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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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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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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management and industrial collaboration. The position will focus primarily on the development and scale-up of innovative recycling approaches for photovoltaic modules and their constituent materials, with
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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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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