Hybrid Master Thesis Intern, AI/ML Algorithms for Network Sensing

Posted last month

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About the role

  • Perform literature review and state-of-the-art analysis of AI/ML algorithms used in radars and sensing devices
  • Analyze advantages and disadvantages of different algorithms for sensing services (qualitative/quantitative analysis)
  • Study and design options for integrating AI/ML into ISAC architecture for different sensing methods (monostatic, multi-static) and devices (BS, UE)
  • Design system architecture for AI/ML integration into ISAC focusing on sensing data processing and sensing outputs derivation
  • Evaluate sensing accuracy using AI/ML algorithms and perform quantitative evaluations
  • Collaborate with highly skilled colleagues in Nokia Standards, contribute to research projects, and produce a Master thesis deliverable

Requirements

  • Bachelor degree in communications engineering, information theory, or computer science with a grade of at least 2.0 (German grade system equivalent)
  • Basic knowledge in communication networks, signal processing, and AI/ML applications in communication networks
  • Proficiency in programming for quantitative evaluations (e.g., Matlab, Python, C)
  • Experience in software engineering (Design Patterns, object oriented programming)
  • Highly proficient in spoken and written English
  • Ability to work independently and collaborate in diverse teams
  • Willingness and ability to learn new skills and engage in novel disruptive research areas

Benefits

  • Continuous learning opportunities
  • Well-being programs to support mental and physical health
  • Opportunities to join and get supported by employee resource groups
  • Mentoring programs
  • Highly diverse teams with an inclusive and empowering culture
  • Commitment to inclusion and equal opportunity employment

Job title

Master Thesis Intern, AI/ML Algorithms for Network Sensing

Job type

Experience level

Entry level

Salary

Not specified

Degree requirement

Bachelor's Degree

Tech skills

Location requirements

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