Job Overview
Role: Research Intern (Wireless & AI) Location: Bangalore, Karnataka Experience: Freshers (Enrolled Students) Qualification: M.E / M.Tech / M.Sc / PhD Key Skills: Wireless Comm, AI/ML, Python, C++, SDR, 5G/6G
Job Description
For the Nokia Internship 2026 program, Bell Labs is looking for a research intern to work on AI-driven wireless communications. You will collaborate with a global team to prototype AI-native 6G networks using software-defined radios (SDR), open-source cellular stacks, and GPU-accelerated edge AI platforms.
The role offers hands-on experience in developing and deploying ML-based wireless components, conducting Over-the-Air (OTA) experiments, and contributing to real-time prototypes alongside top researchers.
Roles and Responsibilities
As a Research Intern at Nokia Bell Labs, your key responsibilities will include:
- Prototyping: Developing functionalities in a machine-learning-based next-generation wireless networks prototyping framework.
- AI/ML Deployment: Optimizing and deploying AI/ML models on GPU/accelerated edge devices.
- SDR Operations: Configuring and operating SDR (Software Defined Radio) hardware for baseband processing and OTA experiments.
- Research: Designing experiments investigating AI-native waveforms, channel estimation, and adaptive communication schemes.
- Collaboration: Collaborating with Radio Systems researchers to merge wireless communications with embedded systems.
Skills and Eligibility Criteria
To be eligible for Nokia Internship 2026, candidates must meet the following criteria:
- Educational Background: Enrolment in a Master’s or PhD program in Electrical Engineering, Computer Science, Telecommunications, or related disciplines.
- Mandatory Technical Skills:
- Solid foundation in Wireless Communications and computer networks.
- Strong programming skills in Python and C++.
- Comfortable working with Linux, embedded devices, and open-source projects.
- Preferred Skills (Nice to have):
- Understanding of 4G/5G NR PHY/MAC procedures.
- Experience deploying ML models on embedded GPU platforms.
- Familiarity with RF calibration and real-world OTA testing.
- Contributions to open-source projects or peer-reviewed research.