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models in the context of neuromuscular diseases. Activities include: - Development of signal processing libraries and extraction of neuromuscular disease biomarkers; - Collection of electrophysiological
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experience with machine learning libraries (e.g., PyTorch, Scikit-learn, Hugging Face Transformers) and tools for efficient software development (e.g., Co-pilot, Cursor). Desirable: Basic knowledge of data
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microservices and containerisation (e.g., Docker, Kubernetes), integration with Hugging Face, familiarity with machine learning libraries (e.g., PyTorch, Scikit-learn), and proficiency with tools supporting
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