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HUHuawei Research Center Germany & Austria

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

München
Full-timeWorking StudentOn-site
AI/ML

Adapting secure multiparty computation libraries with novel primitives for distributed ML at global ICT solutions provider. Enrolled Master's student in EE, informatics, or telecommunications required. Collaboration with multidisciplinary teams.

Requirements

  • Motivation and creativity
  • Strong technical background in machine learning or secure multiparty computation
  • 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 written and spoken English

Tasks

  • Investigate new 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 research findings at academic conferences
  • Present research results to the academic community
  • 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

Informal Culture

  • Innovative culture and team spirit
  • Diverse and welcoming environment
  • Competent and motivated team

Learning & Development

  • Global knowledge exchange network
  • Broad range of training opportunities
  • Online and face-to-face training
  • German and Mandarin language courses

Free or Subsidized Food

  • Company canteen with diverse meals

Purpose-Driven Work

  • Self-responsible work
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