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on emerging privacy-preserving techniques such as homomorphic encryption, secure multi-party computation and federate learning. Key Responsibilities: Conduct advanced research in the areas of privacy-preserving
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Continental Automotive Singapore on emerging privacy-preserving techniques such as homomorphic encryption, secure multi-party computation and federate learning. Key Responsibilities: Work closely with Centre’s
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). • Strong understanding of security practices in cloud environments (IAM, encryption, firewalls). • Excellent problem-solving skills and ability to work independently or as part of a team. Preferred
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-driven security strategies, quantum-safe encryption, and threat intelligence? Do you thrive on mentoring future leaders, influencing industry best practices, and staying ahead of emerging cyber threats
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, on AI Safety and Trust Technology, especially on the topic of applying secure multi-party computation, homomorphic encryption, and federated learning in privacy-preserving machine learning. The successful
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environments) is advantageous Understanding of application security principles, secure coding practices, and common vulnerabilities (e.g. OWASP Top 10, authentication/authorization, data encryption) will be
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security, and encryption technologies. Familiarity with network protocols, system hardening, and secure coding practices. Experience in incident response and forensic investigations to identify, contain, and