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into a working MVP fast enough to support the next grant application round. Main duties and responsibilities Rebuild the RVI scoring engine as clean, standalone Python code, implementing the validated
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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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) 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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. 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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verifiable outcomes, such as mathematics, code, tool-use, and reasoning. Develop reward modeling, reward calibration and verifier-based training. Generate and validate synthetic or gym training tasks. Run
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this new hybrid network. Your code will directly enable the next generation of energy-efficient AI clusters. Project scope You will bridge the gap between custom optical hardware and standard AI software