Multimodal Biometric Research Specialist

1 week ago

Singapore beBeeBiometric Full time $90,000 - $120,000
Job Opportunity">

We are seeking a talented Research Professional to join our team. This is an exciting opportunity for someone who wants to make a difference in the field of biometric research.

The successful candidate will lead the research and development of secure and privacy-preserving multimodal biometric authentication systems for mobile devices using federated learning. They will work closely with industry partners to advance real-world applications in mobile security and user identity verification.

Key Responsibilities:

  • Lead and conduct research on federated learning methodologies for multimodal biometric authentication on mobile devices, emphasizing privacy-preserving techniques and real-world deployment.
  • Develop and evaluate federated models that operate under positive-label-only constraints on local devices, focusing on scenarios where user templates are authentic and unimodal/multimodal verification must be robust against spoofing or deepfakes.
  • Collaborate closely with the Principal Investigator (PI) to execute the project's research plan, including literature review, algorithm design, experiment design, model training, evaluation, and benchmarking.

Requirements:

  • Ph.D. degree in Computer Science, Electrical/Electronic Engineering, Information Systems, or a related field with a strong research focus in machine learning, biometrics, or mobile computing.
  • Proven experience in federated learning, privacy-preserving machine learning, or distributed AI systems.
  • Familiarity with biometric authentication systems, especially involving multimodal signals such as face, voice, and fingerprint recognition.

Benefits:

  • Opportunity to contribute to cutting-edge research in the field of biometric authentication.
  • Chance to work with a multidisciplinary team and collaborate with industry partners.
  • Professional growth and development opportunities.

Key Competencies:

  • Research Independence – Ability to design and lead experiments, analyze results, and iterate on solutions with minimal supervision.
  • Technical Proficiency – Strong skills in machine learning, federated learning, and biometric systems, with practical coding proficiency in Python and relevant ML frameworks.
  • Problem Solving – Able to identify technical challenges and formulate innovative, scalable, and privacy-aware solutions in real-world mobile settings.

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