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; collaborate with the research teams at EPFL and Imperial College London Design, implement, and maintain core components of the verified LLM inference engine, including the runtime and glue code connecting
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the smooth operation of the various video-conferencing systems during events Provide support and advice to users, evaluate and select software and IT equipment, procure and set up equipment, customize and
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code Developing agentic AI workflows for specification autoformalization, proof generation, and proof repair Build a strong network in the fields of formal verification, systems, and ML infrastructure
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) Ensuring medical grade software quality following industry best practices for patients' usage at home and for researchers in rehabilitation facilities Designing, coding, and driving the automation of test
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reconstruction Develop methods for behavior understanding from multi-view video and audio recordings Advance multimodal large language models for fine-grained action understanding and reasoning Help shape the next
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to redefine how machines interpret human actions, anticipate intentions, and interact seamlessly with people in various settings. The successful candidate will be developing new methods for Real-time Video
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the restitution workshops held in year 4. Contribute to the production of the Vertical Talks video capsules and podcasts, together with the project team and the local partners. Scientific production Publish at
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. Participating in code reviews to ensure code quality and to provide & receive feedback. Applying IT security best practices, including e.g. Zero Trust and Least Privilege principles. Working with clients
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. Main duties and responsibilities Extract and harden a scoring engine from an existing Python/Streamlit prototype into robust, standalone code Rebuild the data layer from Neo4j to a Python-native graph
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