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HUHuawei Research Center Germany & Austria

Master Thesis Student - Privacy-Enhancing Technologies for Collaborative AI(m/w/x)

München
Full-timeWorking StudentOn-site
AI/ML
Data Science

Investigating privacy-preserving methods for distributed machine learning, adapting secure multiparty computation libraries for a global ICT solutions provider. Enrolled Master’s student in electrical engineering, informatics, or telecommunications, with strong machine learning background, required. German and Mandarin language courses, healthy canteen meals.

Requirements

  • Motivated and creative Master’s student
  • Strong technical background in machine learning
  • Curiosity for new technologies
  • Desire to make a difference
  • Enrolled Master’s student in electrical engineering, informatics, telecommunications, or related field
  • In-depth experience with machine learning or secure multiparty computation
  • Proficiency in Python and C++
  • Fluent in written and spoken English

Tasks

  • Investigate privacy-preserving methods for distributed machine learning
  • Adapt secure multiparty computation libraries with novel primitives
  • Develop machine-learning use cases using secure multiparty computation
  • Test machine-learning use cases for performance and security
  • Collaborate with multidisciplinary teams on innovative projects
  • Publish and present research findings at academic conferences
  • Contribute to the generation of intellectual property

Education

  • Currently in higher education

Languages

  • EnglishBusiness Fluent

Tools & Technologies

  • Python
  • C++
  • Machine learning
  • Secure multiparty computation

Benefits

Free or Subsidized Food

  • Healthy canteen meals

Learning & Development

  • Broad training opportunities
  • German language courses
  • Mandarin language courses

Informal Culture

  • Diverse and welcoming environment

Purpose-Driven Work

  • Self-responsible work
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