Work mediated through digital labour platforms is expanding rapidly across Europe, with algorithmic management increasingly shaping how tasks are allocated, monitored and evaluated. Platform work can offer flexibility and labour market access, but it also raises occupational safety concerns, particularly for workers often classified as self-employed and therefore not fully covered by traditional occupational health and safety legislation. Algorithmic management can create incentives for unsafe behaviour, intensify work pace, reduce autonomy and shift risks to workers, while platforms and software designers may not systematically consider OSH implications in their systems. At the same time, emerging EU policy initiatives, including proposals addressing platform work and algorithmic management, may change responsibilities and enforcement mechanisms, yet their practical OSH consequences remain insufficiently understood. Existing prevention approaches are challenged by limited visibility on platform working conditions and by the multi-actor nature of platform ecosystems involving platforms, workers, clients and regulators. This project addresses these gaps by analysing legal, technical and learning-based instruments that can improve occupational safety in platform work, with a focus on actionable prevention guidance for platforms and workers and on how algorithmic management can be leveraged to support safer work.