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Huawei Research Center Germany & Austria
yesterday

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

München
Full-timeWorking StudentOn-site
AI/ML

Description

You will drive innovation in AI privacy by developing secure machine learning methods and collaborating with expert teams to publish research and generate new intellectual property.

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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

Education

Currently in higher education

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

Tools & Technologies

PythonC++Machine learningSecure multiparty computation

Languages

EnglishBusiness Fluent

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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